2014
DOI: 10.1109/mpul.2014.2309582
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Advanced Technology Meets Mental Health: How smartphones, textile electronics, and signal processing can serve mental health monitoring, diagnosis, and treatment

Abstract: Mental disorders, characterized by impaired emotional and mood balance, are common in the West. Recent surveys have found that millions of people (age 18?65) have experienced some kind of mental disorder, such as psychotic disorder, major depression, bipolar disorder, panic disorder, social phobia, and somatoform disorder [1]. Specifically, in 2010, 164.8 million people in Europe were affected by such illnesses [1].

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Cited by 9 publications
(7 citation statements)
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“…Regarding the second aim, our results con rm the importance of tailoring and personalization in digital monitoring tools (e.g. Saunders et al, 2017;Valenza, Lanatà, Paradiso, & Scilingo, 2014). First, customization can be used in the form of patients being able to add text or photos.…”
Section: Discussionsupporting
confidence: 56%
“…Regarding the second aim, our results con rm the importance of tailoring and personalization in digital monitoring tools (e.g. Saunders et al, 2017;Valenza, Lanatà, Paradiso, & Scilingo, 2014). First, customization can be used in the form of patients being able to add text or photos.…”
Section: Discussionsupporting
confidence: 56%
“…According to Valenza et al [ 64 ], studying mood swings over time shows that changes in mental status have intrinsic dynamics, which suggests a link between autonomous nervous system dynamics (a division of peripheral nervous system) and bipolar disorders. These changes can be shown in physiological parameters such as respiration activity, heart rate variability (HRV), and electrodermal activity.…”
Section: Resultsmentioning
confidence: 99%
“…The results showed great potential in monitoring parameters relevant to the course of affective disorders, although most of the reviewed studies were feasibility tests or pilot trials without control groups, conducted with only a small number of participants and with short assessment periods, and did not investigating any medium- or long-term effects or possible risks of the respective applications. It is important to highlight that there are several systems described in publications that could not be included in this review due to: not meeting the inclusion criteria (eg, no monitoring of objective data [ 73 , 74 ]), not involving a smartphone for the objective monitoring [ 64 , 69 , 75 - 77 ], not having studied participants with an affective disorder diagnosis [ 78 - 81 ], or not having published results from trials being conducted at the time of our search [ 82 ].…”
Section: Discussionmentioning
confidence: 99%
“…Signal processing can be used on large scale multimodal datasets to identify hidden attributes from the raw sensor data. Signal processing techniques can be beneficial once raw sensor data has been collected as they have previously measured atypical speech for people with autism [154], measured depression using heartbeat dynamics [155] and detected common physiological signals associated with bipolar disorder [156].…”
Section: Data Analytics and Datasetsmentioning
confidence: 99%