Smartphone-based Device for Checking Mental Status in Real Time

Oyama‐Higa, Mayumi; Wang, Wenbiao; Kaizu, Shigeo; Futaba, Terufumi; Suzuki, Taira

doi:10.5220/0005655401370142

Cited by 4 publications

(3 citation statements)

References 3 publications

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“…For instance, Li et al [93] achieved a 99.1% accuracy discriminating depressed and nondepressed participants based on EEG. Other systems monitoring body temperature [94], saliva [95], autonomic nerve balance [96], and facial muscle activities [97] could also be relevant. However, because these sensor modalities are not mobile or wearable to any great extent, they were excluded.…”

Section: Discussionmentioning

confidence: 99%

Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

Rohani

Faurholt‐Jepsen

Kessing

et al. 2018

JMIR Mhealth Uhealth

168

146

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BackgroundSeveral studies have recently reported on the correlation between objective behavioral features collected via mobile and wearable devices and depressive mood symptoms in patients with affective disorders (unipolar and bipolar disorders). However, individual studies have reported on different and sometimes contradicting results, and no quantitative systematic review of the correlation between objective behavioral features and depressive mood symptoms has been published.ObjectiveThe objectives of this systematic review were to (1) provide an overview of the correlations between objective behavioral features and depressive mood symptoms reported in the literature and (2) investigate the strength and statistical significance of these correlations across studies. The answers to these questions could potentially help identify which objective features have shown most promising results across studies.MethodsWe conducted a systematic review of the scientific literature, reported according to the preferred reporting items for systematic reviews and meta-analyses guidelines. IEEE Xplore, ACM Digital Library, Web of Sciences, PsychINFO, PubMed, DBLP computer science bibliography, HTA, DARE, Scopus, and Science Direct were searched and supplemented by hand examination of reference lists. The search ended on April 27, 2017, and was limited to studies published between 2007 and 2017.ResultsA total of 46 studies were eligible for the review. These studies identified and investigated 85 unique objective behavioral features, covering 17 various sensor data inputs. These features were divided into 7 categories. Several features were found to have statistically significant and consistent correlation directionality with mood assessment (eg, the amount of home stay, sleep duration, and vigorous activity), while others showed directionality discrepancies across the studies (eg, amount of text messages [short message service] sent, time spent between locations, and frequency of mobile phone screen activity).ConclusionsSeveral studies showed consistent and statistically significant correlations between objective behavioral features collected via mobile and wearable devices and depressive mood symptoms. Hence, continuous and everyday monitoring of behavioral aspects in affective disorders could be a promising supplementary objective measure for estimating depressive mood symptoms. However, the evidence is limited by methodological issues in individual studies and by a lack of standardization of (1) the collected objective features, (2) the mood assessment methodology, and (3) the statistical methods applied. Therefore, consistency in data collection and analysis in future studies is needed, making replication studies as well as meta-analyses possible.

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Section: Discussionmentioning

confidence: 99%

Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

Rohani

Faurholt‐Jepsen

Kessing

et al. 2018

JMIR Mhealth Uhealth

168

146

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“…By this means, the users can effectively adapt themselves to the external environment and stay mentally healthy [31]. …”

Section: Development Of Smartphone-based Device For Self-check In mentioning

confidence: 99%

Indication of Mental Health from Fingertip Pulse Waves and Its Application

Oyama‐Higa¹,

Ou²

2018

Journal of Healthcare Engineering

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This article is a comprehensive review of recent studies of the authors on the indication of mental health from biological information contained in pulse waves. A series of studies discovered that the largest Lyapunov exponent (LLE) of the attractor, which is constructed for the time series data from pulse waves, can provide as an effective indicator of mental health. A low level of LLE indicates insufficiency of external adaptability, which is characteristic of dementia and depression sufferers. On the contrary, a continuous high level of LLE indicates excessive external adaptability, and people in this condition tend to resort to violence. With this discovery, real-time display of the LLE, combined with other physiological indexes such as the autonomic nerve balance (ANB), sample entropy, and vascular age, as a reference, can enable people to conduct self-check of mental status. To this end, software development was performed in order to enable users to conduct pulse wave measurement anywhere at any time and display the analytical results in real time during the measurement.

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“…Other systems monitoring e.g. body temperature [81], saliva [82], autonomic nerve balance [83] , and facial muscle activities [84] could also be relevant. However, since these sensor modalities are not mobile or wearable to any great extent, they were excluded.…”

Section: Other Sensor Modalitiesmentioning

confidence: 99%

Correlations between objective behavioral features collected from mobile and wearable devices, and depressive mood symptoms in affective disorders: A systematic review (Preprint)

Rohani¹,

Faurholt‐Jepsen²,

Kessing³

et al. 2017

Preprint

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Background: A number of studies have recently reported on the correlation between objective behavioral features collected via mobile and wearable technologies and mood symptoms in affective disorders (unipolar disorder and bipolar disorder). However, individual studies have reported on different and sometimes contradicting results and no quantitative systematic review of the correlation between objective behavioral features and mood symptoms has been published. Objective: The objectives of this systematic review were to 1) provide an overview of correlations between objective behavioral features and mood symptoms reported in the literature, and 2) investigate the strength and statistical significance of these correlations across studies. The answers to these questions could potentially help in the identification on which objective features have shown most promising results across studies. Methods: A systematic review of the scientific literature, reported according to the Preferred Reporting items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines was conducted. IEEE Xplore, ACM Digital Library, Web of Sciences, PsychINFO, Pubmed, DBLP computer science bibliography, HTA, DARE, Scopus and Science Direct were searched and supplemented by hand examination of reference lists. The search was limited to studies published 2007-2017. Results: A total of 34 studies were eligible for the present review. They investigated 71 unique objective features divided into six different types covering 16 various sensor data inputs. Several objective features were found to have consistent correlation directionality with mood assessment (e.g., the amount of home stay, sleep duration, vigorous activity), while others showed directionality discrepancies across the studies (e.g., amount of SMS sent, time you spend between locations, frequency of smartphone screen activity).

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Smartphone-based Device for Checking Mental Status in Real Time

Cited by 4 publications

References 3 publications

Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review

Indication of Mental Health from Fingertip Pulse Waves and Its Application

Correlations between objective behavioral features collected from mobile and wearable devices, and depressive mood symptoms in affective disorders: A systematic review (Preprint)

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