Assistive Technologies for Bipolar Disorder: A Survey
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paper_title: Predicting Mood Changes in Bipolar Disorder Through Heartbeat Nonlinear Dynamics

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Bipolar disorder (BD) is characterized by an alternation of mood states from depression to (hypo)mania. Mixed states, i.e., a combination of depression and mania symptoms at the same time, can also be present. The diagnosis of this disorder in the current clinical practice is based only on subjective interviews and questionnaires, while no reliable objective psycho-physiological markers are available. Furthermore, there are no biological markers predicting BD outcomes, or providing information about the future clinical course of the phenomenon. To overcome this limitation, here we propose a methodology predicting mood changes in BD using heartbeat nonlinear dynamics exclusively, derived from the ECG. Mood changes are here intended as transitioning between two mental states: euthymic state (EUT), i.e., the good affective balance, and non-euthymic (non-EUT) states. Heart rate variability (HRV) series from 14 bipolar spectrum patients (age: 33.43 $\pm$ 9.76, age range: 23–54; six females) involved in the European project PSYCHE, undergoing whole night electrocardiogram (ECG) monitoring were analyzed. Data were gathered from a wearable system comprised of a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire ECGs. Each patient was monitored twice a week, for 14 weeks, being able to perform normal (unstructured) activities. From each acquisition, the longest artifact-free segment of heartbeat dynamics was selected for further analyses. Sub-segments of 5 min of this segment were used to estimate trends of HRV linear and nonlinear dynamics. Considering data from a current observation at day $t_0$ , and past observations at days ( $t_{-1}$ , $t_{-2}$ ,...,), personalized prediction accuracies in forecasting a mood state (EUT/non-EUT) at day $t_{+1}$ were 69% on average, reaching values as high as 83.3%. This approach opens to the possibility of predicting mood states in bipolar patients through heartbeat nonlinear dynamics exclusively.
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paper_title: A systematic review of the evidence of the burden of bipolar disorder in Europe

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BackgroundBipolar disorder is recognized as a major mental health issue, and its economic impact has been examined in the United States. However, there exists a general scarcity of published studies and lack of standardized data on the burden of the illness across European countries. In this systematic literature review, we highlight the epidemiological, clinical, and economic outcomes of bipolar disorder in Europe.MethodsA systematic review of publications from the last 10 years relating to the burden of bipolar disorder was conducted, including studies on epidemiology, patient-related issues, and costs.ResultsData from the UK, Germany, and Italy indicated a prevalence of bipolar disorder of ~1%, and a misdiagnosis rate of 70% from Spain. In one study, up to 75% of patients had at least one DSM-IV comorbidity, commonly anxiety disorders and substance/alcohol abuse. Attempted suicide rates varied between 21%–54%. In the UK, the estimated rate of premature mortality of patients with bipolar I disorder was 18%. The chronicity of bipolar disorder exerted a profound and debilitating effect on the patient. In Germany, 70% of patients were underemployed, and 72% received disability payments. In Italy, 63%–67% of patients were unemployed. In the UK, the annual costs of unemployment and suicide were £1510 million and £179 million, respectively, at 1999/2000 prices. The estimated UK national cost of bipolar disorder was £4.59 billion, with hospitalization during acute episodes representing the largest component.ConclusionBipolar disorder is a major and underestimated health problem in Europe. A number of issues impact on the economic burden of the disease, such as comorbidities, suicide, early death, unemployment or underemployment. Direct costs of bipolar disorder are mainly associated with hospitalization during acute episodes. Indirect costs are a major contributor to the overall economic burden but are not always recognized in research studies.
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paper_title: A systematic review of the evidence of the burden of bipolar disorder in Europe

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BackgroundBipolar disorder is recognized as a major mental health issue, and its economic impact has been examined in the United States. However, there exists a general scarcity of published studies and lack of standardized data on the burden of the illness across European countries. In this systematic literature review, we highlight the epidemiological, clinical, and economic outcomes of bipolar disorder in Europe.MethodsA systematic review of publications from the last 10 years relating to the burden of bipolar disorder was conducted, including studies on epidemiology, patient-related issues, and costs.ResultsData from the UK, Germany, and Italy indicated a prevalence of bipolar disorder of ~1%, and a misdiagnosis rate of 70% from Spain. In one study, up to 75% of patients had at least one DSM-IV comorbidity, commonly anxiety disorders and substance/alcohol abuse. Attempted suicide rates varied between 21%–54%. In the UK, the estimated rate of premature mortality of patients with bipolar I disorder was 18%. The chronicity of bipolar disorder exerted a profound and debilitating effect on the patient. In Germany, 70% of patients were underemployed, and 72% received disability payments. In Italy, 63%–67% of patients were unemployed. In the UK, the annual costs of unemployment and suicide were £1510 million and £179 million, respectively, at 1999/2000 prices. The estimated UK national cost of bipolar disorder was £4.59 billion, with hospitalization during acute episodes representing the largest component.ConclusionBipolar disorder is a major and underestimated health problem in Europe. A number of issues impact on the economic burden of the disease, such as comorbidities, suicide, early death, unemployment or underemployment. Direct costs of bipolar disorder are mainly associated with hospitalization during acute episodes. Indirect costs are a major contributor to the overall economic burden but are not always recognized in research studies.
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paper_title: Suicide and other causes of mortality in bipolar disorder: a longitudinal study

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Background. The high risk of suicide in bipolar disorder is well recognized, but may have been overestimated. There is conflicting evidence about deaths from other causes and little known about risk factors for suicide. We aimed to estimate suicide and mortality rates in a cohort of bipolar patients and to identify risk factors for suicide. Method. All patients who presented for the first time with a DSM-IV diagnosis of bipolar I disorder in a defined area of southeast London over a 35-year period (1965–1999) were identified. Mortality rates were compared with those of the 1991 England and Wales population, indirectly standardized for age and gender. Univariate and multivariate analyses were used to test potential risk factors for suicide. Results. Of the 239 patients in the cohort, 235 (98·3%) were traced. Forty-two died during the 4422 person-years of follow-up, eight from suicide. The standardized mortality ratio (SMR) for suicide was 9·77 [95% confidence interval (CI) 4·22–19·24], which, although significantly elevated compared to the general population, represented a lower case fatality than expected from previous literature. Deaths from all other causes were not excessive for the age groups studied in this cohort. Alcohol abuse [hazard ratio (HR) 6·81, 95% CI 1·69–27·36, p =0·007] and deterioration from pre-morbid level of functioning up to a year after onset (HR 5·20, 95% CI 1·24–21·89, p =0·024) were associated with increased risk of suicide. Conclusions. Suicide is significantly increased in unselected bipolar patients but actual case fatality is not as high as previously claimed. A history of alcohol abuse and deterioration in function predict suicide in bipolar disorder.
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paper_title: Suicide attempts in bipolar I and bipolar II disorder: a review and meta-analysis of the evidence

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Novick DM, Swartz HA, Frank E. Suicide attempts in bipolar I and bipolar II disorder: a review and meta-analysis of the evidence. Bipolar Disord 2010: 12: 1–9. © 2010 The Authors. ::: Journal compilation © 2010 John Wiley & Sons A/S. ::: ::: Objective: The prevalence of suicide attempts (SA) in bipolar II disorder (BPII), particularly in comparison to the prevalence in bipolar I disorder (BPI), is an understudied and controversial issue with mixed results. To date, there has been no comprehensive review of the published prevalence data for attempted suicide in BPII. ::: ::: Methods: We conducted a literature review and meta-analysis of published reports that specified the proportion of individuals with BPII in their presentation of SA data. Systematic searching yielded 24 reports providing rates of SA in BPII and 21 reports including rates of SA in both BPI and BPII. We estimated the prevalence of SA in BPII by combining data across reports of similar designs. To compare rates of SA in BPII and BPI, we calculated a pooled odds ratio (OR) and 95% confidence interval (CI) with random-effect meta-analytic techniques with retrospective data from 15 reports that detailed rates of SA in both BPI and BPII. ::: ::: Results: Among the 24 reports with any BPII data, 32.4% (356/1099) of individuals retrospectively reported a lifetime history of SA, 19.8% (93/469) prospectively reported attempted suicide, and 20.5% (55/268) of index attempters were diagnosed with BPII. In 15 retrospective studies suitable for meta-analysis, the prevalence of attempted suicide in BPII and BPI was not significantly different: 32.4% and 36.3%, respectively (OR = 1.21, 95% CI: 0.98–1.48, p = 0.07). ::: ::: Conclusion: The contribution of BPII to suicidal behavior is considerable. Our findings suggest that there is no significant effect of bipolar subtype on rate of SA. Our findings are particularly alarming in concert with other evidence, including (i) the well-documented predictive role of SA for completed suicide and (ii) the evidence suggesting that individuals with BPII use significantly more violent and lethal methods than do individuals with BPI. To reduce suicide-related morbidity and mortality, routine clinical care for BPII must include ongoing risk assessment and interventions targeted at risk factors.
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paper_title: Costs of Bipolar Disorder

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Bipolar disorder is a chronic affective disorder that causes significant economic burden to patients, families and society. It has a lifetime prevalence of approximately 1.3%. Bipolar disorder is characterised by recurrent mania or hypomania and depressive episodes that cause impairments in functioning and health-related quality of life. Patients require acute and maintenance therapy delivered via inpatient and outpatient treatment. Patients with bipolar disorder often have contact with the social welfare and legal systems; bipolar disorder impairs occupational functioning and may lead to premature mortality through suicide. This review examines the symptomatology of bipolar disorder and identifies those features that make it difficult and costly to treat. Methods for assessing direct and indirect costs are reviewed. We report on comprehensive cost studies as well as administrative claims data and program evaluations. The majority of data is drawn from studies conducted in the US; however, we discuss European studies when appropriate. Only two comprehensive cost-of-illness studies on bipolar disorder, one prevalence-based and one incidence-based, have been reported. There are, however, several comprehensive cost-of-illness studies measuring economic burden of affective disorders including bipolar disorder. Estimates of total costs of affective disorders in the US range from $US30.4-43.7 billion (1990 values). In the prevalence-based cost-of-illness study on bipolar disorder, total annual costs were estimated at $US45.2 billion (1991 values). In the incidence-based study, lifetime costs were estimated at $US24 billion. Although there have been recent advances in pharmacotherapy and outpatient therapy, hospitalisation still accounts for a substantial portion of the direct costs. A variety of outpatient services are increasingly important for the care of patients with bipolar disorder and costs in this area continue to grow. Indirect costs due to morbidity and premature mortality comprise a large portion of the cost of illness. Lost workdays or inability to work due to the disease cause high morbidity costs. Intangible costs such as family burden and impaired health-related quality of life are common, although it has proved difficult to attach monetary values to these costs.
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paper_title: The 16-Item quick inventory of depressive symptomatology (QIDS), clinician rating (QIDS-C), and self-report (QIDS-SR): a psychometric evaluation in patients with chronic major depression

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Abstract Background The 16-item Quick Inventory of Depressive Symptomatology (QIDS), a new measure of depressive symptom severity derived from the 30-item Inventory of Depressive Symptomatology (IDS), is available in both self-report (QIDS-SR 16 ) and clinician-rated (QIDS-C 16 ) formats. Methods This report evaluates and compares the psychometric properties of the QIDS-SR 16 in relation to the IDS-SR 30 and the 24-item Hamilton Rating Scale for Depression (HAM-D 24 ) in 596 adult outpatients treated for chronic nonpsychotic, major depressive disorder. Results Internal consistency was high for the QIDS-SR 16 (Cronbach's α = .86), the IDS-SR 30 (Cronbach's α = .92), and the HAM-D 24 (Cronbach's α = .88). QIDS-SR 16 total scores were highly correlated with IDS-SR 30 (.96) and HAM-D 24 (.86) total scores. Item–total correlations revealed that several similar items were highly correlated with both QIDS-SR 16 and IDS-SR 30 total scores. Roughly 1.3 times the QIDS-SR 16 total score is predictive of the HAM-D 17 (17-item version of the HAM-D) total score. Conclusions The QIDS-SR 16 was as sensitive to symptom change as the IDS-SR 30 and HAM-D 24 , indicating high concurrent validity for all three scales. The QIDS-SR 16 has highly acceptable psychometric properties, which supports the usefulness of this brief rating of depressive symptom severity in both clinical and research settings.
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paper_title: Current Use of Depression Rating Scales in Mental Health Setting

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Objective ::: This study was to investigate the current use of depression rating scales by psychiatrists and clinical psychologists in Korea.
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paper_title: Carer distress : A prospective, population-based study

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This study investigates whether transitions into and out of unpaid caregiving are associated with increased risk for onset of or delayed recovery from psychological distress, and traces the prevalence of distress across successive years of caring activity and after caregiving has ceased. The analysis is based on data from the British Household Panel Survey covering 3000 would-be carers, 2900 former carers, and 11,100 non-carers during the 1990s; their psychological well-being was assessed at annual intervals using the General Health Questionnaire. Carers providing long hours of care over extended spells present raised levels of distress, women more so than men. Compared with non-carers, risk for onset of distress increases progressively with the amount of time devoted to caregiving each week. Adverse effects on the psychological well-being of heavily involved carers are most pronounced around the start of their care episodes and when caregiving ends. Ongoing care increases their susceptibility to recurring distress, and adverse health effects are evident beyond the end of their caregiving episodes. Several groups of carers experience psychological health inequalities compared with non-carers, especially those looking after a spouse or partner, and mothers caring for a sick or disabled child. The findings underline the importance for effective carer support and health promotion of early identification of carers, monitoring high risk groups, timing appropriate interventions, and targeting resources.
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paper_title: Assessment Scales in Depression, Mania and Anxiety

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The first brief chapter in this book rehearses the arguments for using rating scales routinely in evidence-based practice in order to evaluate effectiveness, inform treatment choice and improve outcomes. Scales are also useful to highlight or detect symptoms that might be missed by a more
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paper_title: Novel Technology as Platform for Interventions for caregivers and individuals with Severe Mental Health Illnesses: A Systematic Review

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Abstract Background Severe mental illnesses (SMIs) have been found to be associated with both increases in morbidity-mortality, need for treatment care in patients themselves, and burden for relatives as caregivers. A growing number of web-based and mobile software applications have appeared that aim to address various barriers with respect to access to care. Our objective was to review and summarize recent advancements in such interventions for caregivers of individuals with a SMI. Methods We conducted a systematic search for papers evaluating interactive mobile or web-based software (using no or only minimal support from a professional) specifically aimed at supporting informal caregivers. We also searched for those supporting patients with SMI so as to not to miss any which might include relatives. Results Out of a total of 1673 initial hits, we identified 11 articles reporting on 9 different mobile or web-based software programs. The main result is that none of those studies focused on caregivers, and the ones we identified using mobile or web-based applications were just for patients and not their relatives. Limitations Differentiating between online and offline available software might not always have been totally reliable, and we might have therefore missed some studies. Conclusions In summary, the studies provided evidence that remotely accessible interventions for patients with SMI are feasible and acceptable to patients. No such empirically evaluated program was available for informal caregivers such as relatives. Keeping in mind the influential role of those informal caregivers in the process of treatment and self-management, this is highly relevant for public health. Supporting informal caregivers can improve well-being of both caregivers and patients.
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paper_title: Mobile Interventions for Severe Mental Illness: Design and Preliminary Data from Three Approaches

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Mobile devices can be used to deliver psychosocial interventions, yet there is little prior application in severe mental illness. We provide the rationale, design, and preliminary data from three ongoing clinical trials of mobile interventions developed for bipolar disorder or schizophrenia. Project 1 used a personal digital assistant to prompt engagement in personalized self-management behaviors based on real-time data. Project 2 employed experience sampling via text messages to facilitate case management. Project 3 built on group functional skills training for schizophrenia by incorporating between-session mobile phone contacts with therapists. Preliminary findings were of minimal participant attrition, and no broken devices; yet, several operational and technical barriers needed to be addressed. Adherence was similar to that reported in non-psychiatric populations, with high participant satisfaction. Thus, mobile devices appear feasible and acceptable in augmenting psychosocial interventions for severe mental illness, with future research in establishing efficacy, cost-effectiveness, and ethical and safety protocols.
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paper_title: Beating Bipolar: exploratory trial of a novel Internet-based psychoeducational treatment for bipolar disorder.

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OBJECTIVES ::: Psychoeducational approaches are promising interventions for the long-term management of bipolar disorder. In consultation with professionals, patients, and their families we have developed a novel web-based psychoeducational intervention for bipolar disorder called Beating Bipolar. We undertook a preliminary exploratory randomized trial to examine efficacy, feasibility and acceptability. ::: ::: ::: METHODS ::: This was an exploratory randomized controlled trial of Beating Bipolar (current controlled trials registration number: ISRCTN81375447). The control arm was treatment-as-usual and the a priori primary outcome measure was quality of life [measured by the brief World Health Organization Quality of Life (WHOQOL-BREF) scale]. Secondary outcomes included psychosocial functioning, insight, depressive and manic symptoms and relapse, and use of healthcare resources. Fifty participants were randomized to either the Beating Bipolar intervention plus treatment-as-usual or just treatment-as-usual. The intervention was delivered over a four-month period and outcomes were assessed six months later. ::: ::: ::: RESULTS ::: There was no significant difference between the intervention and control groups on the primary outcome measure (total WHOQOL-BREF score) but there was a modest improvement within the psychological subsection of the WHOQOL-BREF for the intervention group relative to the control group. There were no significant differences between the groups on any of the secondary outcome measures. ::: ::: ::: CONCLUSIONS ::: Beating Bipolar is potentially a safe and engaging intervention which can be delivered remotely to large numbers of patients with bipolar disorder at relatively low cost. It may have a modest effect on psychological quality of life. Further work is required to establish the impact of this intervention on insight, knowledge, treatment adherence, self-efficacy and self-management skills.
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paper_title: Designing mobile health technology for bipolar disorder: a field trial of the monarca system

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An increasing number of pervasive healthcare systems are being designed, that allow people to monitor and get feedback on their health and wellness. To address the challenges of self-management of mental illnesses, we have developed the MONARCA system - a personal monitoring system for bipolar patients. We conducted a 14 week field trial in which 12 patients used the system, and we report findings focusing on their experiences. The results were positive; compared to using paper-based forms, the adherence to self-assessment improved; the system was considered very easy to use; and the perceived usefulness of the system was high. Based on this study, the paper discusses three HCI questions related to the design of personal health technologies; how to design for disease awareness and self-treatment, how to ensure adherence to personal health technologies, and the roles of different types of technology platforms.
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paper_title: Keeping therapies simple: psychoeducation in the prevention of relapse in affective disorders

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Psychological interventions for mood disorders can be divided into ‘ skilled’ and ‘simple’. Psychoeducation belongs to the latter group: a simple and illness-focused therapy with prophylactic efficacy in all major mood disorders. Successful implementation of psychoeducation requires a proper setting, including open-door policy, team effort and empowerment of the therapeutic alliance.
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paper_title: IntelliCare: An Eclectic, Skills-Based App Suite for the Treatment of Depression and Anxiety

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Background: Digital mental health tools have tended to use psychoeducational strategies based on treatment orientations developed and validated outside of digital health. These features do not map well to the brief but frequent ways that people use mobile phones and mobile phone apps today. To address these challenges, we developed a suite of apps for depression and anxiety called IntelliCare, each developed with a focused goal and interactional style. IntelliCare apps prioritize interactive skills training over education and are designed for frequent but short interactions. Objective: The overall objective of this study was to pilot a coach-assisted version of IntelliCare and evaluate its use and efficacy at reducing symptoms of depression and anxiety. Methods: Participants, recruited through a health care system, Web-based and community advertising, and clinical research registries, were included in this single-arm trial if they had elevated symptoms of depression or anxiety. Participants had access to the 14 IntelliCare apps from Google Play and received 8 weeks of coaching on the use of IntelliCare. Coaching included an initial phone call plus 2 or more texts per week over the 8 weeks, with some participants receiving an additional brief phone call. Primary outcomes included the Patient Health Questionnaire-9 (PHQ-9) for depression and the Generalized Anxiety Disorder-7 (GAD-7) for anxiety. Participants were compensated up to US $90 for completing all assessments; compensation was not for app use or treatment engagement. Results: Of the 99 participants who initiated treatment, 90.1% (90/99) completed 8 weeks. Participants showed substantial reductions in the PHQ-9 and GAD-7 (P<.001). Participants used the apps an average of 195.4 (SD 141) times over the 8 weeks. The average length of use was 1.1 (SD 2.1) minutes, and 95% of participants downloaded 5 or more of the IntelliCare apps. Conclusions: This study supports the IntelliCare framework of providing a suite of skills-focused apps that can be used frequently and briefly to reduce symptoms of depression and anxiety. The IntelliCare system is elemental, allowing individual apps to be used or not used based on their effectiveness and utility, and it is eclectic, viewing treatment strategies as elements that can be applied as needed rather than adhering to a singular, overarching, theoretical model. Trial Registration: Clinicaltrials.gov NCT02176226; http://clinicaltrials.gov/ct2/show/NCT02176226 (Archived by WebCite at http://www.webcitation/6mQZuBGk1) [J Med Internet Res 2017;19(1):e10]
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paper_title: Mobile technology for medication adherence in people with mood disorders: A systematic review

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Abstract Background Medication non-adherence is a critical challenge for many patients diagnosed with mood disorders (Goodwin and Jamison, 1990). There is a need for alternative strategies that improve adherence among patients with mood disorders that are cost-effective, able to reach large patient populations, easy to implement, and that allow for communication with patients outside of in-person visits. Technology-based approaches to promote medication adherence are increasingly being explored to address this need. The aim of this paper is to provide a systematic review of the use of mobile technologies to improve medication adherence in patients with mood disorders. Methods A total of nine articles were identified as describing mobile technology targeting medication adherence in mood disorder populations. Results Results showed overall satisfaction and feasibility of mobile technology, and reduction in mood symptoms; however, few examined effectiveness of mobile technology improving medication adherence through randomized control trials. Limitations Given the limited number of studies, further research is needed to determine long term effectiveness. Conclusions Mobile technologies has the potential to improve medication adherence and can be further utilized for symptom tracking, side effects tracking, direct links to prescription refills, and provide patients with greater ownership over their treatment progress.
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paper_title: Monitoring activity of patients with bipolar disorder using smart phones

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Mobile computing is changing the landscape of clinical monitoring and self-monitoring. One of the major impacts will be in healthcare, where increase in number of sensing modalities is providing more and more information on the state of overall wellbeing, behaviour and health. There are numerous applications of mobile computing that range from wellbeing applications, such as physical fitness, stress or burnout up to applications that target mental disorders including bipolar disorder. Use of information provided by mobile computing devices can track the state of the subjects and also allow for experience sampling in order to gather subjective information. This paper reports on the results obtained from a medical trial with monitoring of bipolar disorder patients and how the episodes of the diseases correlate to the analysis of the data sampled from mobile phone acting as a monitoring device.
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paper_title: Mobile phones as medical devices in mental disorder treatment: an overview

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Mental disorders can have a significant, nega- tive impact on sufferers' lives, as well as on their friends and family, healthcare systems and other parts of society. Approximately 25 % of all people in Europe and the USA experience a mental disorder at least once in their lifetime. Currently, monitoring mental disorders relies on subjective clinical self-reporting rating scales, which were developed more than 50 years ago. In this paper, we discuss how mobile phones can support the treatment of mental disor- ders by (1) implementing human-computer interfaces to support therapy and (2) collecting relevant data from patients' daily lives to monitor the current state and development of their mental disorders. Concerning the first point, we review various systems that utilize mobile phones for the treatment of mental disorders. We also evaluate how their core design features and dimensions can be applied in other, similar systems. Concerning the second point, we highlight the feasibility of using mobile phones to collect comprehensive data including voice data, motion and location information. Data mining methods are also reviewed and discussed. Based on the presented studies, we summarize advantages and drawbacks of the most prom- ising mobile phone technologies for detecting mood dis- orders like depression or bipolar disorder. Finally, we discuss practical implementation details, legal issues and business models for the introduction of mobile phones as medical devices.
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paper_title: Advances in Electrodermal Activity Processing with Applications for Mental Health

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This book explores Autonomic Nervous System (ANS) dynamics as investigated through Electrodermal Activity (EDA) processing. It presents groundbreaking research in thetechnical field of biomedical engineering, especially biomedical signal processing, as well as clinical fields ofpsychometrics, affective computing, and psychological assessment. This volumedescribes some of the most complete, effective, and personalized methodologies for extracting data from a non-stationary, nonlinear EDA signal in order to characterize the affective and emotional state of a human subject. These methodologies are underscored by discussion of real-world applications in mood assessment. The text also examines the physiological bases of emotion recognition through noninvasivemonitoring of the autonomic nervous system. This is an ideal book forbiomedical engineers, physiologists,neuroscientists, engineers, applied mathmeticians, psychiatric and psychological clinicians, and graduate students in these fields. This book also:Expertly introduces a novel approach for EDA analysis based on convex optimization and sparsity, a topic of rapidly increasing interestAuthoritatively presents groundbreaking research achieved using EDA as an exemplarybiomarker of ANS dynamicsDeftly exploresEDA's potential as a source of reliable and effective markers for the assessment of emotional responses in healthy subjects,as well as for the recognition of pathological mood states in bipolar patients
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paper_title: Smartphone-centred wearable sensors network for monitoring patients with bipolar disorder

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Bipolar Disorder is a severe form of mental illness. It is characterized by alternated episodes of mania and depression, and it is treated typically with a combination of pharmacotherapy and psychotherapy. Recognizing early warning signs of upcoming phases of mania or depression would be of great help for a personalized medical treatment. Unfortunately, this is a difficult task to be performed for both patient and doctors. In this paper we present the MONARCA wearable system, which is meant for recognizing early warning signs and predict maniac or depressive episodes. The system is a smartphone-centred and minimally invasive wearable sensors network that is being developing in the framework of the MONARCA European project.
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paper_title: Towards long term monitoring of electrodermal activity in daily life

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Manic depression, also known as bipolar disorder, is a common and severe form of mental disorder. The European research project MONARCA aims at developing and validating mobile technologies for multi-parametric, long term monitoring of physiological and behavioral information relevant to bipolar disorder. One aspect of MONARCA is to investigate the long term monitoring of Electrodermal activity (EDA) to support the diagnosis and treatment of bipolar disorder patients. EDA is known as an indicator of the emotional state and the stress level of a person. To realize a long-term monitoring of the EDA, the integration of the sensor system in the shoe or sock is a promising approach. This paper presents a first step towards such a sensor system. In a feasibility study including 8 subjects, we investigate the correlation between EDA measurements at the fingers, which is the most established sensing site, with measurements of the EDA at the feet. The results indicate that 88% of the evoked skin conductance responses (SCRs) occur at both sensing sites. When using an action movie as psychophysiologically activating stimulus, we have found weaker reactivity in the foot than in the hand EDA. The results also suggest that the influence of moderate physical activity on EDA measurements is low and has a similar effect for both recording sites. This suggests that the foot recording location is suitable for recordings in daily life even in the presence of moderate movement.
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paper_title: Decomposition of skin conductance data by means of nonnegative deconvolution

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Skin conductance (SC) data are usually characterized by a sequence of overlapping phasic skin conductance responses (SCRs) overlying a tonic component. The variability of SCR shapes hereby complicates the proper decomposition of SC data. A method is proposed for full decomposition of SC data into tonic and phasic components. A two-compartment diffusion model was found to adequately describe a standard SCR shape based on the process of sweat diffusion. Nonnegative deconvolution is used to decompose SC data into discrete compact responses and at the same time assess deviations from the standard SCR shape, which could be ascribed to the additional process of pore opening. Based on the result of single non-overlapped SCRs, response parameters can be estimated precisely as shown in a paradigm with varying inter-stimulus intervals.
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paper_title: Predicting Mood Changes in Bipolar Disorder Through Heartbeat Nonlinear Dynamics

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Bipolar disorder (BD) is characterized by an alternation of mood states from depression to (hypo)mania. Mixed states, i.e., a combination of depression and mania symptoms at the same time, can also be present. The diagnosis of this disorder in the current clinical practice is based only on subjective interviews and questionnaires, while no reliable objective psycho-physiological markers are available. Furthermore, there are no biological markers predicting BD outcomes, or providing information about the future clinical course of the phenomenon. To overcome this limitation, here we propose a methodology predicting mood changes in BD using heartbeat nonlinear dynamics exclusively, derived from the ECG. Mood changes are here intended as transitioning between two mental states: euthymic state (EUT), i.e., the good affective balance, and non-euthymic (non-EUT) states. Heart rate variability (HRV) series from 14 bipolar spectrum patients (age: 33.43 $\pm$ 9.76, age range: 23–54; six females) involved in the European project PSYCHE, undergoing whole night electrocardiogram (ECG) monitoring were analyzed. Data were gathered from a wearable system comprised of a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire ECGs. Each patient was monitored twice a week, for 14 weeks, being able to perform normal (unstructured) activities. From each acquisition, the longest artifact-free segment of heartbeat dynamics was selected for further analyses. Sub-segments of 5 min of this segment were used to estimate trends of HRV linear and nonlinear dynamics. Considering data from a current observation at day $t_0$ , and past observations at days ( $t_{-1}$ , $t_{-2}$ ,...,), personalized prediction accuracies in forecasting a mood state (EUT/non-EUT) at day $t_{+1}$ were 69% on average, reaching values as high as 83.3%. This approach opens to the possibility of predicting mood states in bipolar patients through heartbeat nonlinear dynamics exclusively.
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paper_title: Heart rate variability in bipolar mania and schizophrenia

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Background: Autonomic nervous system (ANS) dysfunction and reduced heart rate variability (HRV) have been reported in a wide variety of psychiatric disorders, but have not been well characterized in bipolar mania. We recorded cardiac activity and assessed HRV in acutely hospitalized manic bipolar (BD) and schizophrenia (SCZ) patients compared to age- and gender-matched healthy comparison (HC) subjects. Method: HRV was assessed using time domain, frequency domain, and nonlinear analyses in 23 manic BD, 14 SCZ, and 23 HC subjects during a 5 min rest period. Psychiatric symptoms were assessed by administration of the Brief Psychiatric Rating Scale (BPRS) and the Young Mania Rating Scale (YMRS). Results: Manic BD patients demonstrated a significant reduction in HRV, parasympathetic activity, and cardiac entropy compared to HC subjects, while SCZ patients demonstrated a similar, but non-significant, trend towards lower HRV and entropy. Reduction in parasympathetic tone was significantly correlated with higher YMRS scores and the unusual thought content subscale on the BPRS. Decreased entropy was associated with increased aggression and diminished personal hygiene on the YMRS scale. Conclusion: Cardiac function in manic BD individuals is characterized by decreased HRV, reduced vagal tone, and a decline in heart rate complexity as assessed by linear and nonlinear methods of analysis. Autonomic dysregulation is associated with more severe psychiatric symptoms, suggesting HRV dysfunction in this disorder may be dependent on the phase of the illness.
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paper_title: Heart Rate Variability as an Index of Regulated Emotional Responding

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The study of individual differences in emotional responding can provide considerable insight into interpersonal dynamics and the etiology of psychopathology. Heart rate variability (HRV) analysis is emerging as an objective measure of regulated emotional responding (generating emotional responses of appropriate timing and magnitude). This review provides a theoretical and empirical rationale for the use of HRV as an index of individual differences in regulated emotional responding. Two major theoretical frameworks that articulate the role of HRV in emotional responding are presented, and relevant empirical literature is reviewed. The case is made that HRV is an accessible research tool that can increase the understanding of emotion in social and psychopathological processes.
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paper_title: Wearable Monitoring for Mood Recognition in Bipolar Disorder Based on History-Dependent Long-Term Heart Rate Variability Analysis

paper_content:

Current clinical practice in diagnosing patients affected by psychiatric disorders such as bipolar disorder is based only on verbal interviews and scores from specific questionnaires, and no reliable and objective psycho-physiological markers are taken into account. In this paper, we propose to use a wearable system based on a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire electrocardiogram, respirogram, and body posture information in order to detect a pattern of objective physiological parameters to support diagnosis. Moreover, we implemented a novel ad hoc methodology of advanced biosignal processing able to effectively recognize four possible clinical mood states in bipolar patients (i.e., depression, mixed state, hypomania, and euthymia) continuously monitored up to 18 h, using heart rate variability information exclusively. Mood assessment is intended as an intrasubject evaluation in which the patient's states are modeled as a Markov chain, i.e., in the time domain, each mood state refers to the previous one. As validation, eight bipolar patients were monitored collecting and analyzing more than 400 h of autonomic and cardiovascular activity. Experimental results demonstrate that our novel concept of personalized and pervasive monitoring constitutes a viable and robust clinical decision support system for bipolar disorders recognizing mood states with a total classification accuracy up to 95.81%.
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paper_title: Sleep disorders as core symptoms of depression

paper_content:

Links between sleep and depression are strong. About three quarters of depressed patients have insomnia symptoms, and hypersomnia is present in about 40% of young depressed adults and 10% of older patients, with a preponderance in females. The symptoms cause huge distress, have a major impact on quality of life, and are a strong risk factor for suicide. As well as the subjective experience of sleep symptoms, there are well-documented changes in objective sleep architecture in depression. Mechanisms of sleep regulation and how they might be disturbed in depression are discussed. The sleep symptoms are often unresolved by treatment, and confer a greater risk of relapse and recurrence. Epidemiological studies have pointed out that insomnia in nondepressed subjects is a risk factor for later development of depression. There is therefore a need for more successful management of sleep disturbance in depression, in order to improve quality of life in these patients and reduce an important factor in depressive relapse and recurrence.
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paper_title: Hypersomnia subtypes, sleep and relapse in bipolar disorder.

paper_content:

Background ::: Though poorly defined, hypersomnia is associated with negative health outcomes, and new-onset and recurrence of psychiatric illness. Lack of definition impedes generalizability across studies. The present research clarifies hypersomnia diagnoses in bipolar disorder by exploring possible subgroups and their relationship to prospective sleep data and relapse into mood episodes.
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paper_title: Rate of switch from depression into mania after therapeutic sleep deprivation in bipolar depression

paper_content:

Sleep deprivation is a potentially useful non-pharmacological treatment for depression. A relationship between sleep loss and the onset of mania has been reported, so it is possible that a switch from depression into mania after sleep deprivation might be expected in bipolar depressed patients who are treated with sleep deprivation. In a sample of 206 bipolar depressed treated with three cycles of sleep deprivation, alone or in combination with heterogeneous medications, we observed a 4.85% switch rate into mania and a 5.83% switch rate into hypomania. These percentages are comparable to those observed with antidepressant drug treatments.
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paper_title: Can home-monitoring of sleep predict depressive episodes in bipolar patients?

paper_content:

The aim of this study is the evaluation of the autonomic regulations during depressive stages in bipolar patients in order to test new quantitative and objective measures to detect such events. A sensorized T-shirt was used to record ECG signal and body movements during the night, from which HRV data and sleep macrostructure were estimated and analyzed. 9 out of 20 features extracted resulted to be significant (p<;0.05) in discriminating among depressive and non-depressive states. Such features are representation of HRV dynamics in both linear and non-linear domain and parameters linked to sleep modulations.
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paper_title: Designing mobile health technology for bipolar disorder: a field trial of the monarca system

paper_content:

An increasing number of pervasive healthcare systems are being designed, that allow people to monitor and get feedback on their health and wellness. To address the challenges of self-management of mental illnesses, we have developed the MONARCA system - a personal monitoring system for bipolar patients. We conducted a 14 week field trial in which 12 patients used the system, and we report findings focusing on their experiences. The results were positive; compared to using paper-based forms, the adherence to self-assessment improved; the system was considered very easy to use; and the perceived usefulness of the system was high. Based on this study, the paper discusses three HCI questions related to the design of personal health technologies; how to design for disease awareness and self-treatment, how to ensure adherence to personal health technologies, and the roles of different types of technology platforms.
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paper_title: Smartphone-centred wearable sensors network for monitoring patients with bipolar disorder

paper_content:

Bipolar Disorder is a severe form of mental illness. It is characterized by alternated episodes of mania and depression, and it is treated typically with a combination of pharmacotherapy and psychotherapy. Recognizing early warning signs of upcoming phases of mania or depression would be of great help for a personalized medical treatment. Unfortunately, this is a difficult task to be performed for both patient and doctors. In this paper we present the MONARCA wearable system, which is meant for recognizing early warning signs and predict maniac or depressive episodes. The system is a smartphone-centred and minimally invasive wearable sensors network that is being developing in the framework of the MONARCA European project.
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paper_title: PSYCHE: Personalised monitoring systems for care in mental health

paper_content:

One of the areas of great demand for the need of continuous monitoring, patient participation and medical prediction is that of mood disorders, more specifically bipolar disorders. Due to the unpredictable and episodic nature of bipolar disorder, it is necessary to take the traditional standard procedures of mood assessment through the administration of rating scales and questionnaires and integrate this with tangible data found in emerging research on central and peripheral changes in brain function that may be associated to the clinical status and response to treatment throughout the course of bipolar disorder. This paper presents PSYCHE system, a personal, cost-effective, multi-parametric monitoring system based on textile platforms and portable sensing devices for the long term and short term acquisition of data from selected class of patients affected by mood disorders. The acquired data will be processed and analyzed in the established platform that takes into account the Electronic Health Records (EHR) of the patient, a personalized data referee system, as well as medical analysis in order to verify the diagnosis and help in prognosis of the illness. Constant feedback and monitoring will be used to manage the illness, to give patients support, to facilitate interaction between patient and physician as well as to alert professionals in case of patients relapse and depressive or manic episodes income, as the ultimate goal is to identify signal trends indicating detection and prediction of critical events.
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paper_title: Staging Bipolar Disorder

paper_content:

The purpose of this study was to analyze the evidence supporting a staging model for bipolar disorder. The authors conducted an extensive Medline and Pubmed search of the published literature using a variety of search terms (staging, bipolar disorder, early intervention) to find relevant articles, which were reviewed in detail. Only recently specific proposals have been made to apply clinical staging to bipolar disorder. The staging model in bipolar disorder suggests a progression from prodromal (at-risk) to more severe and refractory presentations (Stage IV). A staging model implies a longitudinal appraisal of different aspects: clinical variables, such as number of episodes and subsyndromal symptoms, functional and cognitive impairment, comorbidity, biomarkers, and neuroanatomical changes. Staging models are based on the fact that response to treatment is generally better when it is introduced early in the course of the illness. It assumes that earlier stages have better prognosis and require simpler therapeutic regimens. Staging may assist in bipolar disorder treatment planning and prognosis, and emphasize the importance of early intervention. Further research is required in this exciting and novel area.
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paper_title: Framework to Predict Bipolar Episodes

paper_content:

Patients suffering from Bipolar disorder (BD) experience repeated relapses of depressive and manic states. The extremity of this disorder can lead to many unpleasant events, even suicide attempts, which make early detection vital. Presently, the primary method for identifying these states is evaluation by psychiatrists based on patient’s self-reporting. However, ubiquitous use of mobile devices in combination with sensor fusion has the potential to provide a faster and convenient alternative mode of diagnosis to better manage the illness. This paper proposes a continuous, autonomous sensor fusion based monitoring framework to identify and predict state changes in patients suffering from bipolar disorder. Instead of relying on subjective self-reported data, the proposed system uses sensors to measure and collect, Heart Rate Variability, Quantity and Quality of sleep and Electrodermal activity data as predictors to discern between the two bipolar states. Using classification techniques along with a fusion algorithm, a prediction algorithm can be derived based on all the sensor modalities, gathered via a mobile application, is used to set alerts and visualize the information and results efficiently.
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paper_title: Why Don't Psychiatrists Use Scales to Measure Outcome When Treating Depressed Patients?

paper_content:

OBJECTIVE ::: A survey of psychiatrists in the United Kingdom found that only a minority routinely used standardized measures to assess outcome when treating depression and anxiety disorders. The goals of the present study were to determine how frequently psychiatrists in the United States use scales to measure outcome when treating depressed patients and, for those clinicians who do not regularly use such scales, to ascertain the reasons for the lack of use. ::: ::: ::: METHOD ::: The subjects were 314 psychiatrists who attended a continuing medical education conference in California, Massachusetts, New York, or Wisconsin in 2006 or 2007. Prior to a lecture, the subjects completed a questionnaire that included 2 questions regarding the use of rating scales to monitor outcome when treating depression. ::: ::: ::: RESULTS ::: More than 80% of the psychiatrists indicated that they did not routinely use scales to monitor outcome when treating depression. The most frequent reasons psychiatrists gave for not using scales were that they did not believe scales would be clinically helpful, that scales take too much time to use, and that they were not trained in the use of such measures. ::: ::: ::: CONCLUSIONS ::: The majority of psychiatrists indicated that they do not routinely use standardized measures to evaluate outcome when treating depressed patients. The Centers for Medicare and Medicaid Services' Physician Quality Reporting Initiative is intended to improve quality of care by providing physicians financial incentives to document outcomes reflecting best practices. If standardized outcome assessment is to assume increasing importance in this country, either educational efforts or payor mandates, or both, will be necessary to change clinicians' behavior.
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paper_title: Psychiatrists in the UK do not use outcomes measures: National survey

paper_content:

Governmental policy statements on mental health practice over the past decade have emphasised the importance of routinely measuring individual patient outcomes (Department of Health, [1991][1], [1998][2]; [Secretary of State for Health, 1999][3]). Despite the availability of various standardised
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paper_title: Heart rate variability in bipolar mania and schizophrenia

paper_content:

Background: Autonomic nervous system (ANS) dysfunction and reduced heart rate variability (HRV) have been reported in a wide variety of psychiatric disorders, but have not been well characterized in bipolar mania. We recorded cardiac activity and assessed HRV in acutely hospitalized manic bipolar (BD) and schizophrenia (SCZ) patients compared to age- and gender-matched healthy comparison (HC) subjects. Method: HRV was assessed using time domain, frequency domain, and nonlinear analyses in 23 manic BD, 14 SCZ, and 23 HC subjects during a 5 min rest period. Psychiatric symptoms were assessed by administration of the Brief Psychiatric Rating Scale (BPRS) and the Young Mania Rating Scale (YMRS). Results: Manic BD patients demonstrated a significant reduction in HRV, parasympathetic activity, and cardiac entropy compared to HC subjects, while SCZ patients demonstrated a similar, but non-significant, trend towards lower HRV and entropy. Reduction in parasympathetic tone was significantly correlated with higher YMRS scores and the unusual thought content subscale on the BPRS. Decreased entropy was associated with increased aggression and diminished personal hygiene on the YMRS scale. Conclusion: Cardiac function in manic BD individuals is characterized by decreased HRV, reduced vagal tone, and a decline in heart rate complexity as assessed by linear and nonlinear methods of analysis. Autonomic dysregulation is associated with more severe psychiatric symptoms, suggesting HRV dysfunction in this disorder may be dependent on the phase of the illness.
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paper_title: Current Use of Depression Rating Scales in Mental Health Setting

paper_content:

Objective ::: This study was to investigate the current use of depression rating scales by psychiatrists and clinical psychologists in Korea.
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paper_title: Smartphone-centred wearable sensors network for monitoring patients with bipolar disorder

paper_content:

Bipolar Disorder is a severe form of mental illness. It is characterized by alternated episodes of mania and depression, and it is treated typically with a combination of pharmacotherapy and psychotherapy. Recognizing early warning signs of upcoming phases of mania or depression would be of great help for a personalized medical treatment. Unfortunately, this is a difficult task to be performed for both patient and doctors. In this paper we present the MONARCA wearable system, which is meant for recognizing early warning signs and predict maniac or depressive episodes. The system is a smartphone-centred and minimally invasive wearable sensors network that is being developing in the framework of the MONARCA European project.
---
paper_title: Wearable Monitoring for Mood Recognition in Bipolar Disorder Based on History-Dependent Long-Term Heart Rate Variability Analysis

paper_content:

Current clinical practice in diagnosing patients affected by psychiatric disorders such as bipolar disorder is based only on verbal interviews and scores from specific questionnaires, and no reliable and objective psycho-physiological markers are taken into account. In this paper, we propose to use a wearable system based on a comfortable t-shirt with integrated fabric electrodes and sensors able to acquire electrocardiogram, respirogram, and body posture information in order to detect a pattern of objective physiological parameters to support diagnosis. Moreover, we implemented a novel ad hoc methodology of advanced biosignal processing able to effectively recognize four possible clinical mood states in bipolar patients (i.e., depression, mixed state, hypomania, and euthymia) continuously monitored up to 18 h, using heart rate variability information exclusively. Mood assessment is intended as an intrasubject evaluation in which the patient's states are modeled as a Markov chain, i.e., in the time domain, each mood state refers to the previous one. As validation, eight bipolar patients were monitored collecting and analyzing more than 400 h of autonomic and cardiovascular activity. Experimental results demonstrate that our novel concept of personalized and pervasive monitoring constitutes a viable and robust clinical decision support system for bipolar disorders recognizing mood states with a total classification accuracy up to 95.81%.
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paper_title: A Bipolar Disorder Monitoring System Based on Wearable Device and Smartphone

paper_content:

Abstract: The growing aging population and the increasingly healthcare costs demand a new paradigm for the healthcare system, which must focus on patient and emphasize mainly prevention, not only treatment. In this context, and with the wide availability of mobile technology, we here propose a patient monitoring system based on wearable sensors, and connected to a medical datacenter through a mobile device. Patients with bipolar disorder can benefit from this remote monitoring system, as warning signs can be detected early, preventing a hospitalization. Studies have reported that great part of those diagnosed with bipolar disorder do not report recognizing any early warning signs. Thus, to prevent relapses, in our system, predictive information associated with warning signs are sent to the patient's doctor. This paper proposes a continuous monitoring system of the patients movement amount, including quality of sleep, through a system composed of wearable device, patient's smartphone and a web application.
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paper_title: Mobile Interventions for Severe Mental Illness: Design and Preliminary Data from Three Approaches

paper_content:

Mobile devices can be used to deliver psychosocial interventions, yet there is little prior application in severe mental illness. We provide the rationale, design, and preliminary data from three ongoing clinical trials of mobile interventions developed for bipolar disorder or schizophrenia. Project 1 used a personal digital assistant to prompt engagement in personalized self-management behaviors based on real-time data. Project 2 employed experience sampling via text messages to facilitate case management. Project 3 built on group functional skills training for schizophrenia by incorporating between-session mobile phone contacts with therapists. Preliminary findings were of minimal participant attrition, and no broken devices; yet, several operational and technical barriers needed to be addressed. Adherence was similar to that reported in non-psychiatric populations, with high participant satisfaction. Thus, mobile devices appear feasible and acceptable in augmenting psychosocial interventions for severe mental illness, with future research in establishing efficacy, cost-effectiveness, and ethical and safety protocols.
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paper_title: Smartphone-centred wearable sensors network for monitoring patients with bipolar disorder

paper_content:

Bipolar Disorder is a severe form of mental illness. It is characterized by alternated episodes of mania and depression, and it is treated typically with a combination of pharmacotherapy and psychotherapy. Recognizing early warning signs of upcoming phases of mania or depression would be of great help for a personalized medical treatment. Unfortunately, this is a difficult task to be performed for both patient and doctors. In this paper we present the MONARCA wearable system, which is meant for recognizing early warning signs and predict maniac or depressive episodes. The system is a smartphone-centred and minimally invasive wearable sensors network that is being developing in the framework of the MONARCA European project.
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Title: Assistive Technologies for Bipolar Disorder: A Survey
Section 1: INTRODUCTION
Description 1: This section introduces bipolar disorder, its different states, and provides an overview of the paper's structure.

Section 2: SEVERITY ACROSS THE GLOBE
Description 2: This section provides worldwide statistics on the prevalence, mortality rates, and socioeconomic burden of bipolar disorder.

Section 3: CURRENT SYSTEM IN PLACE
Description 3: This section discusses the existing methods for diagnosing and treating bipolar disorder, including common rating scales and psychiatric interviews.

Section 4: BEHAVIORAL INTERVENTION TECHNOLOGIES
Description 4: This section introduces various behavioral intervention technologies, such as internet-based psychotherapies, web-based and mobile-based interventions, and psychoeducation.

Section 5: ONGOING RESEARCHES TO INFER BIPOLAR STATE
Description 5: This section covers ongoing research on using biomarkers to predict bipolar states, with subsections on social interaction and physical motion, electrodermal activity, heart rate variability, and sleep patterns.

Section 6: CASE STUDIES AND PROJECTS
Description 6: This section details two significant projects, MONARCA and PSYCHE, that contribute to the monitoring, treatment, and prediction of bipolar disorder.

Section 7: EVOLUTION
Description 7: This section reviews the evolution of technologies aimed at assisting bipolar disorder and the shift in research focus over the past decade.

Section 8: DISCUSSION
Description 8: This section summarizes the findings of the paper, discusses the effectiveness and user adherence to current technologies, and identifies gaps in research.

Section 9: FUTURE WORK
Description 9: This section highlights the future directions for research, including challenges and potential improvements for personalized monitoring systems and Body Area Networks (BAN).