Current Advances in Wearable Devices and Their Sensors in Patients With Depression

Overview

Journal Front Psychiatry

Specialty Psychiatry

Date 2021 Jul 5

PMID 34220580

Citations 24

Authors

Seunggyu Lee

Hyewon Kim

Mi Jin Park

Hong Jin Jeon

Affiliations

Soon will be listed here.

Abstract

In this study, a literature survey was conducted of research into the development and use of wearable devices and sensors in patients with depression. We collected 18 studies that had investigated wearable devices for assessment, monitoring, or prediction of depression. In this report, we examine the sensors of the various types of wearable devices (e.g., actigraphy units, wristbands, fitness trackers, and smartwatches) and parameters measured through sensors in people with depression. In addition, we discuss future trends, referring to research in other areas employing wearable devices, and suggest the challenges of using wearable devices in the field of depression. Real-time objective monitoring of symptoms and novel approaches for diagnosis and treatment using wearable devices will lead to changes in management of patients with depression. During the process, it is necessary to overcome several issues, including limited types of collected data, reliability, user adherence, and privacy concerns.

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References

Rausch J, Johnson M, Corley K, Hobby H, Shendarkar N, Fei Y . Depressed patients have higher body temperature: 5-HT transporter long promoter region effects. Neuropsychobiology. 2003; 47(3):120-7. DOI: 10.1159/000070579. View

Cook J, Prairie M, Plante D . Utility of the Fitbit Flex to evaluate sleep in major depressive disorder: A comparison against polysomnography and wrist-worn actigraphy. J Affect Disord. 2017; 217:299-305. PMC: 5509938. DOI: 10.1016/j.jad.2017.04.030. View

de Mello M, de Aquino Lemos V, Antunes H, Bittencourt L, Santos-Silva R, Tufik S . Relationship between physical activity and depression and anxiety symptoms: a population study. J Affect Disord. 2013; 149(1-3):241-6. DOI: 10.1016/j.jad.2013.01.035. View

Snippe E, Simons C, Hartmann J, Menne-Lothmann C, Kramer I, Booij S . Change in daily life behaviors and depression: Within-person and between-person associations. Health Psychol. 2015; 35(5):433-41. DOI: 10.1037/hea0000312. View

Sadeh A, Acebo C . The role of actigraphy in sleep medicine. Sleep Med Rev. 2003; 6(2):113-24. DOI: 10.1053/smrv.2001.0182. View

Kemp A, Quintana D . The relationship between mental and physical health: insights from the study of heart rate variability. Int J Psychophysiol. 2013; 89(3):288-96. DOI: 10.1016/j.ijpsycho.2013.06.018. View

Morrison L, Yardley L, Powell J, Michie S . What design features are used in effective e-health interventions? A review using techniques from Critical Interpretive Synthesis. Telemed J E Health. 2012; 18(2):137-44. DOI: 10.1089/tmj.2011.0062. View

Griffiths R, Kotschet K, Arfon S, Xu Z, Johnson W, Drago J . Automated assessment of bradykinesia and dyskinesia in Parkinson's disease. J Parkinsons Dis. 2013; 2(1):47-55. DOI: 10.3233/JPD-2012-11071. View

Sharma A, Mentz R, Granger B, Heitner J, Cooper L, Banerjee D . Utilizing mobile technologies to improve physical activity and medication adherence in patients with heart failure and diabetes mellitus: Rationale and design of the TARGET-HF-DM Trial. Am Heart J. 2019; 211:22-33. DOI: 10.1016/j.ahj.2019.01.007. View

10.

Chung K, Tso K . Relationship between insomnia and pain in major depressive disorder: A sleep diary and actigraphy study. Sleep Med. 2010; 11(8):752-8. DOI: 10.1016/j.sleep.2009.09.005. View

11.

Razavi N, Horn H, Koschorke P, Hugli S, Hofle O, Muller T . Measuring motor activity in major depression: the association between the Hamilton Depression Rating Scale and actigraphy. Psychiatry Res. 2011; 190(2-3):212-6. DOI: 10.1016/j.psychres.2011.05.028. View

12.

Vallance J, Winkler E, Gardiner P, Healy G, Lynch B, Owen N . Associations of objectively-assessed physical activity and sedentary time with depression: NHANES (2005-2006). Prev Med. 2011; 53(4-5):284-8. DOI: 10.1016/j.ypmed.2011.07.013. View

13.

Kruijshaar M, Barendregt J, Vos T, de Graaf R, Spijker J, Andrews G . Lifetime prevalence estimates of major depression: an indirect estimation method and a quantification of recall bias. Eur J Epidemiol. 2005; 20(1):103-11. DOI: 10.1007/s10654-004-1009-0. View

14.

Tazawa Y, Liang K, Yoshimura M, Kitazawa M, Kaise Y, Takamiya A . Evaluating depression with multimodal wristband-type wearable device: screening and assessing patient severity utilizing machine-learning. Heliyon. 2020; 6(2):e03274. PMC: 7005437. DOI: 10.1016/j.heliyon.2020.e03274. View

15.

Dong M, Fang B, Li J, Sun F, Liu H . Wearable sensing devices for upper limbs: A systematic review. Proc Inst Mech Eng H. 2020; 235(1):117-130. DOI: 10.1177/0954411920953031. View

16.

Winkler D, Pjrek E, Lanzenberger R, Baldinger P, Eitel D, Kasper S . Actigraphy in patients with treatment-resistant depression undergoing electroconvulsive therapy. J Psychiatr Res. 2014; 57:96-100. DOI: 10.1016/j.jpsychires.2014.06.006. View

17.

Ward N, DOERR H, Storrie M . Skin conductance: a potentially sensitive test for depression. Psychiatry Res. 1983; 10(4):295-302. DOI: 10.1016/0165-1781(83)90076-8. View

18.

Rojo-Wissar D, McQuaid J, Ancoli-Israel S, Gengler D, Haynes P . Maternal Bonding Predicts Actigraphy-Measured Sleep Parameters in Depressed and Nondepressed Adults. J Nerv Ment Dis. 2019; 208(1):33-37. PMC: 7282245. DOI: 10.1097/NMD.0000000000001071. View

19.

Burns M, Begale M, Duffecy J, Gergle D, Karr C, Giangrande E . Harnessing context sensing to develop a mobile intervention for depression. J Med Internet Res. 2011; 13(3):e55. PMC: 3222181. DOI: 10.2196/jmir.1838. View

20.

Cormack F, McCue M, Taptiklis N, Skirrow C, Glazer E, Panagopoulos E . Wearable Technology for High-Frequency Cognitive and Mood Assessment in Major Depressive Disorder: Longitudinal Observational Study. JMIR Ment Health. 2019; 6(11):e12814. PMC: 6887827. DOI: 10.2196/12814. View