Mobile devices for the remote acquisition of physiological and behavioral biomarkers in psychiatric clinical research.

Psychiatric disorders are linked to a variety of biological, psychological, and contextual causes and consequences. Laboratory studies have elucidated the importance of several key physiological and behavioral biomarkers in the study of psychiatric disorders, but much less is known about the role of these biomarkers in naturalistic settings. These gaps are largely driven by methodological barriers to assessing biomarker data rapidly, reliably, and frequently outside the clinic or laboratory. Mobile health (mHealth) tools offer new opportunities to study relevant biomarkers in concert with other types of data (e.g., self-reports, global positioning system data). This review provides an overview on the state of this emerging field and describes examples from the literature where mHealth tools have been used to measure a wide array of biomarkers in the context of psychiatric functioning (e.g., psychological stress, anxiety, autism, substance use). We also outline advantages and special considerations for incorporating mHealth tools for remote biomarker measurement into studies of psychiatric illness and treatment and identify several specific opportunities for expanding this promising methodology. Integrating mHealth tools into this area may dramatically improve psychiatric science and facilitate highly personalized clinical care of psychiatric disorders.

[1]  Konrad Paul Kording,et al.  Mobile Phone Sensor Correlates of Depressive Symptom Severity in Daily-Life Behavior: An Exploratory Study , 2015, Journal of medical Internet research.

[2]  Yasufumi Mizuno,et al.  Hand-held monitor of sympathetic nervous system using salivary amylase activity and its validation by driver fatigue assessment. , 2006, Biosensors & bioelectronics.

[3]  Emre Ertin,et al.  Continuous inference of psychological stress from sensory measurements collected in the natural environment , 2011, Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks.

[4]  V. Shetty,et al.  Utility of a salivary biosensor for objective assessment of surgery-related stress. , 2012, Journal of oral and maxillofacial surgery : official journal of the American Association of Oral and Maxillofacial Surgeons.

[5]  D. Mariner,et al.  Post-puff respiration measures on smokers of different tar yield cigarettes , 2009, Inhalation Toxicology.

[6]  Lorien C Abroms,et al.  A content analysis of popular smartphone apps for smoking cessation. , 2013, American journal of preventive medicine.

[7]  S. Shiffman,et al.  Ecological momentary assessment. , 2008, Annual review of clinical psychology.

[8]  Lorien C Abroms,et al.  iPhone apps for smoking cessation: a content analysis. , 2011, American journal of preventive medicine.

[9]  Enzo Pasquale Scilingo,et al.  Speech analysis for mood state characterization in bipolar patients , 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[10]  Jesse Dallery,et al.  A web-based contingency management program with adolescent smokers. , 2008, Journal of applied behavior analysis.

[11]  D. Luxton,et al.  mHealth data security: the need for HIPAA-compliant standardization. , 2012, Telemedicine journal and e-health : the official journal of the American Telemedicine Association.

[12]  F Joseph McClernon,et al.  I am your smartphone, and I know you are about to smoke: the application of mobile sensing and computing approaches to smoking research and treatment. , 2013, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[13]  Russell A. McCann,et al.  mHealth for mental health: Integrating smartphone technology in behavioral healthcare. , 2011 .

[14]  Santosh Kumar,et al.  AutoSense: unobtrusively wearable sensor suite for inferring the onset, causality, and consequences of stress in the field , 2011, SenSys.

[15]  Olga V. Demler,et al.  Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the National Comorbidity Survey Replication. , 2005, Archives of general psychiatry.

[16]  C. Gambelunghe,et al.  Sweat testing to monitor drug exposure. , 2013, Annals of clinical and laboratory science.

[17]  Daniel McDuff,et al.  Remote measurement of cognitive stress via heart rate variability , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[18]  Brian D. Kiluk,et al.  Technology-based interventions for the treatment and recovery management of substance use disorders: a JSAT special issue. , 2014, Journal of substance abuse treatment.

[19]  James M. Rehg,et al.  Detecting bids for eye contact using a wearable camera , 2015, 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).

[20]  N. Volkow,et al.  Biomarkers in substance use disorders. , 2015, ACS chemical neuroscience.

[21]  Peter Leijdekkers,et al.  Using sensors and facial expression recognition to personalize emotion learning for autistic children. , 2013, Studies in health technology and informatics.

[22]  Caroline O Cobb,et al.  Facebook Apps for Smoking Cessation: A Review of Content and Adherence to Evidence-Based Guidelines , 2014, Journal of medical Internet research.

[23]  Aleksey Shaporev,et al.  Tension Tamer: delivering meditation with objective heart rate acquisition for adherence monitoring using a smart phone platform. , 2013, Journal of alternative and complementary medicine.

[24]  J. Dallery,et al.  Effects of an Internet-based voucher reinforcement program for smoking abstinence: a feasibility study. , 2005, Journal of applied behavior analysis.

[25]  V. Shetty,et al.  Salivary biosensors for screening trauma-related psychopathology. , 2010, Oral and maxillofacial surgery clinics of North America.

[26]  T. Vos,et al.  Global burden of disease attributable to mental and substance use disorders: findings from the Global Burden of Disease Study 2010 , 2013, The Lancet.

[27]  Dhavan V. Shah,et al.  How Patients Recovering From Alcoholism Use a Smartphone Intervention , 2012, Journal of dual diagnosis.

[28]  Tanzeem Choudhury,et al.  Automatic detection of social rhythms in bipolar disorder , 2016, J. Am. Medical Informatics Assoc..

[29]  D. DeMets,et al.  Biomarkers and surrogate endpoints: Preferred definitions and conceptual framework , 2001, Clinical pharmacology and therapeutics.

[30]  Martina Mueller,et al.  Research Article Development and Validation of a Smartphone Heart Rate Acquisition Application for Health Promotion and Wellness Telehealth Applications , 2011 .

[31]  Tanzeem Choudhury,et al.  Tracking Mental Well-Being: Balancing Rich Sensing and Patient Needs , 2014, Computer.

[32]  Rosalind W. Picard,et al.  Empatica E3 — A wearable wireless multi-sensor device for real-time computerized biofeedback and data acquisition , 2014 .

[33]  Edward Sazonov,et al.  A wearable sensor system for monitoring cigarette smoking. , 2013, Journal of studies on alcohol and drugs.

[34]  Barbara O Rothbaum,et al.  The "PE coach" smartphone application: an innovative approach to improving implementation, fidelity, and homework adherence during prolonged exposure. , 2013, Psychological services.

[35]  Nancy P Barnett Alcohol sensors and their potential for improving clinical care. , 2015, Addiction.

[36]  Rosalind W Picard Recognizing Stress, Engagement, and Positive Emotion , 2015, IUI.

[37]  T. Insel,et al.  Toward the future of psychiatric diagnosis: the seven pillars of RDoC , 2013, BMC Medicine.

[38]  Kyoko Ohashi,et al.  Actigraph measures discriminate pediatric bipolar disorder from attention-deficit/hyperactivity disorder and typically developing controls. , 2016, Journal of child psychology and psychiatry, and allied disciplines.

[39]  James M. Rehg,et al.  Behavioral Imaging and Autism , 2014, IEEE Pervasive Computing.

[40]  Andrea Gaggioli,et al.  Virtual reality and mobile phones in the treatment of generalized anxiety disorders: a phase-2 clinical trial , 2011, Personal and Ubiquitous Computing.

[41]  Corwin M Zigler,et al.  Developmental validation of a point-of-care, salivary α-amylase biosensor , 2011, Psychoneuroendocrinology.

[42]  D. Asch,et al.  Wearable devices as facilitators, not drivers, of health behavior change. , 2015, JAMA.

[43]  N. Petry,et al.  A randomized study of cellphone technology to reinforce alcohol abstinence in the natural environment. , 2013, Addiction.

[44]  Bonnie A. Clough,et al.  Technological adjuncts to enhance current psychotherapy practices: a review. , 2011, Clinical psychology review.

[45]  Shifali Arora,et al.  Privacy and Security in Mobile Health (mHealth) Research , 2014, Alcohol research : current reviews.

[46]  William T Riley,et al.  News from the NIH: using mobile and wireless technologies to improve health , 2013, Translational behavioral medicine.

[47]  Dror Ben-Zeev,et al.  Technology-Based Assessments and Interventions Targeting Psychiatric and Substance Use Disorders: Innovations and Opportunities , 2012 .

[48]  David Elashoff,et al.  The feasibility of ambulatory biosensor measurement of salivary alpha amylase: Relationships with self-reported and naturalistic psychological stress , 2011, Biological Psychology.

[49]  W. Velicer,et al.  Biochemical verification of tobacco use and cessation. , 2002, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[50]  Jesse Dallery,et al.  A mobile-phone-based breath carbon monoxide meter to detect cigarette smoking. , 2014, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[51]  Nancy P Barnett,et al.  Continuous objective monitoring of alcohol use: twenty-first century measurement using transdermal sensors. , 2013, Alcoholism, clinical and experimental research.

[52]  F. Collins,et al.  A new initiative on precision medicine. , 2015, The New England journal of medicine.

[53]  Vaishali Patel,et al.  Consumer Attitudes and Perceptions on mHealth Privacy and Security: Findings From a Mixed-Methods Study , 2015, Journal of health communication.

[54]  Dhavan V. Shah,et al.  How Can Research Keep Up With eHealth? Ten Strategies for Increasing the Timeliness and Usefulness of eHealth Research , 2014, Journal of medical Internet research.

[55]  N. Rose,et al.  Biomarkers in psychiatry , 2009, Nature.

[56]  J. Dallery,et al.  Internet-based contingency management to promote smoking cessation: a randomized controlled study. , 2013, Journal of applied behavior analysis.

[57]  Valérie Gay,et al.  CaptureMyEmotion: A mobile app to improve emotion learning for autistic children using sensors , 2013, Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems.

[58]  Emre Ertin,et al.  puffMarker: a multi-sensor approach for pinpointing the timing of first lapse in smoking cessation , 2015, UbiComp.

[59]  Martin L. Griss,et al.  Activity-Aware Mental Stress Detection Using Physiological Sensors , 2010, MobiCASE.

[60]  J. Dallery,et al.  Effects of internet-based voucher reinforcement and a transdermal nicotine patch on cigarette smoking. , 2007, Journal of applied behavior analysis.

[61]  James G. Murphy,et al.  Contingency management for alcohol use reduction: a pilot study using a transdermal alcohol sensor. , 2011, Drug and alcohol dependence.

[62]  Joel Frohlich,et al.  Electrophysiological biomarkers of diagnosis and outcome in neurodevelopmental disorders. , 2015, Current opinion in neurology.

[63]  M. Dennis,et al.  Mobile contingency management as an adjunctive smoking cessation treatment for smokers with posttraumatic stress disorder. , 2013, Nicotine & tobacco research : official journal of the Society for Research on Nicotine and Tobacco.

[64]  A. Stone,et al.  Bringing the laboratory and clinic to the community: mobile technologies for health promotion and disease prevention. , 2013, Annual review of psychology.

[65]  John Paul Varkey,et al.  Human motion recognition using a wireless sensor-based wearable system , 2012, Personal and Ubiquitous Computing.

[66]  Makoto Sasaki,et al.  Immunosensor with fluid control mechanism for salivary cortisol analysis. , 2013, Biosensors & bioelectronics.

[67]  Rosalind W. Picard,et al.  A Wearable Sensor for Unobtrusive, Long-Term Assessment of Electrodermal Activity , 2010, IEEE Transactions on Biomedical Engineering.

[68]  Mathew Gregoski,et al.  Photoplethysmograph (PPG) derived heart rate (HR) acquisition using an Android smart phone , 2011, Wireless Health.

[69]  Jesse Dallery,et al.  An internet-based abstinence reinforcement smoking cessation intervention in rural smokers. , 2009, Drug and alcohol dependence.

[70]  S. Shiffman,et al.  Novel Technologies to Study Smoking Behavior: Current Developments in Ecological Momentary Assessment , 2015, Current Addiction Reports.

[71]  D. Quested,et al.  The use of actigraphy in the monitoring of sleep and activity in ADHD: A meta-analysis. , 2016, Sleep medicine reviews.

[72]  Bernd Blobel,et al.  pHealth 2013: Proceedings of the 10th International Conference on Wearable Micro and Nano Technologies for Personalized Health , 2013 .

[73]  Michael Kai Petersen,et al.  Smartphones as pocketable labs: visions for mobile brain imaging and neurofeedback. , 2014, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[74]  Audie A Atienza,et al.  Mobile health technology evaluation: the mHealth evidence workshop. , 2013, American journal of preventive medicine.

[75]  James M. Rehg,et al.  Decoding Children's Social Behavior , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.

[76]  Bonnie A. Clough,et al.  Technological adjuncts to increase adherence to therapy: a review. , 2011, Clinical psychology review.

[77]  Lin Zhong,et al.  Proceedings of the 13th international symposium on Information processing in sensor networks , 2014 .

[78]  Rosalind W. Picard,et al.  Real-Time Mobile Detection of Drug Use with Wearable Biosensors: A Pilot Study , 2014, Journal of Medical Toxicology.

[79]  T. Insel The NIMH Research Domain Criteria (RDoC) Project: precision medicine for psychiatry. , 2014, The American journal of psychiatry.

[80]  Jesse Dallery,et al.  Internet-based group contingency management to promote abstinence from cigarette smoking: a feasibility study. , 2011, Drug and alcohol dependence.

[81]  Amy P Abernethy,et al.  Rapid, responsive, relevant (R3) research: a call for a rapid learning health research enterprise , 2013, Clinical and Translational Medicine.

[82]  Lisa A. Marsch,et al.  Leveraging Technology to Enhance Addiction Treatment and Recovery , 2012, Journal of addictive diseases.

[83]  Misha Pavel,et al.  Mobile Health: Revolutionizing Healthcare Through Transdisciplinary Research , 2013, Computer.

[84]  Terence M Keane,et al.  Reducing the Burden of Mental Illness in Military Veterans , 2011, Perspectives on psychological science : a journal of the Association for Psychological Science.

[85]  Akane Sano,et al.  HealthAware: An advice system for stress, sleep, diet and exercise , 2015, 2015 International Conference on Affective Computing and Intelligent Interaction (ACII).

[86]  Daniel Gatica-Perez,et al.  StressSense: detecting stress in unconstrained acoustic environments using smartphones , 2012, UbiComp.

[87]  Oscar Mayora-Ibarra,et al.  Monitoring activity of patients with bipolar disorder using smart phones , 2013, MoMM '13.

[88]  Syed Monowar Hossain,et al.  mPuff: Automated detection of cigarette smoking puffs from respiration measurements , 2012, 2012 ACM/IEEE 11th International Conference on Information Processing in Sensor Networks (IPSN).

[89]  Stephen V Faraone,et al.  Sleep in children with attention-deficit/hyperactivity disorder: meta-analysis of subjective and objective studies. , 2009, Journal of the American Academy of Child and Adolescent Psychiatry.

[90]  Emre Ertin,et al.  cStress: towards a gold standard for continuous stress assessment in the mobile environment , 2015, UbiComp.

[91]  Rosalind W. Picard,et al.  Preliminary Efforts Directed Toward the Detection of Craving of Illicit Substances: The iHeal Project , 2012, Journal of Medical Toxicology.

[92]  Erica K. Yuen,et al.  mHealth: a mechanism to deliver more accessible, more effective mental health care. , 2014, Clinical psychology & psychotherapy.

[93]  Jesse Dallery,et al.  Advances in the psychosocial treatment of addiction: the role of technology in the delivery of evidence-based psychosocial treatment. , 2012, The Psychiatric clinics of North America.

[94]  Oscar Mayora-Ibarra,et al.  Using smart phone mobility traces for the diagnosis of depressive and manic episodes in bipolar patients , 2014, AH.

[95]  Leonidas J. Guibas,et al.  Information Processing in Sensor Networks , 2003, Lecture Notes in Computer Science.

[96]  Ronald S Duman,et al.  Functional Biomarkers of Depression: Diagnosis, Treatment, and Pathophysiology , 2011, Neuropsychopharmacology.

[97]  Rosalind W. Picard,et al.  Empatica E3 — A wearable wireless multi-sensor device for real-time computerized biofeedback and data acquisition , 2014, 2014 4th International Conference on Wireless Mobile Communication and Healthcare - Transforming Healthcare Through Innovations in Mobile and Wireless Technologies (MOBIHEALTH).

[98]  Yixin Chen,et al.  Identifying drug (cocaine) intake events from acute physiological response in the presence of free-living physical activity , 2014, IPSN-14 Proceedings of the 13th International Symposium on Information Processing in Sensor Networks.

[99]  J. Smyth,et al.  Ecological momentary interventions: incorporating mobile technology into psychosocial and health behaviour treatments. , 2010, British journal of health psychology.

[100]  Jesse Dallery,et al.  An Internet-based abstinence reinforcement treatment for cigarette smoking. , 2007, Drug and alcohol dependence.

[101]  J. Bardram,et al.  Smartphone data as an electronic biomarker of illness activity in bipolar disorder , 2015, European Psychiatry.

[102]  D. Mohr,et al.  Harnessing Context Sensing to Develop a Mobile Intervention for Depression , 2011, Journal of medical Internet research.

[103]  Daniel McDuff,et al.  Biophone: Physiology monitoring from peripheral smartphone motions , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[104]  Garrett Mehl,et al.  mHealth innovations as health system strengthening tools: 12 common applications and a visual framework , 2013, Global Health: Science and Practice.

[105]  Misha Pavel,et al.  Advancing the Science of mHealth , 2012, Journal of health communication.

[106]  Dario Pompili,et al.  Laboratory Validation of Inertial Body Sensors to Detect Cigarette Smoking Arm Movements , 2014, Electronics.