Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review

Abstract

Recently, there has been an increase in the production of devices to monitor mental health and stress as means for expediting detection, and subsequent management of these conditions. The objective of this review is to identify and critically appraise the most recent smart devices and wearable technologies used to identify depression, anxiety, and stress, and the physiological process(es) linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilised smart devices and wearable technologies to detect or monitor anxiety, depression, or stress. The included articles that assessed stress and anxiety unanimously used heart rate variability (HRV) parameters for detection of anxiety and stress, with the latter better detected by HRV and electroencephalogram (EGG) together. Electrodermal activity was used in recent studies, with high accuracy for stress detection; however, with questionable reliability. Depression was found to be largely detected using specific EEG signatures; however, devices detecting depression using EEG are not currently available on the market. This systematic review highlights that average heart rate used by many commercially available smart devices is not as accurate in the detection of stress and anxiety compared with heart rate variability, electrodermal activity, and possibly respiratory rate.

What Are We Measuring When We Evaluate Digital Interventions for Improving Lifestyle? A Scoping Meta-Review

“…Innovative digital methods to address this gap are necessary and these areas could benefit from passive sensing data obtained via smartphones and wearable devices, in the same way, step count is used to evaluating PA. Digital phenotyping through these tools allows quantifying the biological stress response in real time ( 116 ). In experimental conditions, algorithms developed based on physiological proxies of the autonomic nervous system activity (e.g., heart rate, body temperature, skin temperature, and conductance) have demonstrated a high accuracy to detect stress ( 117 ). Moreover, smartphone-based episodic audio recordings allow analyses of voice and speech features that may be potential vocal markers of stress ( 118 , 119 ).…”

Stress Watch: The Use of Heart Rate and Heart Rate Variability to Detect Stress: A Pilot Study Using Smart Watch Wearables

“…The present study aimed to determine if HRV could be used to predict the quality of response to acute stress, comparing the general population to medical students, with the intent to contribute data which may aid in developing a physiological algorithm for stress that could be incorporated into wearable technologies. Whilst there are devices in development capable of detecting stress [ 38 ], there is currently no rigorously validated algorithm for stress detection. The current study found a significant rise in LF, HF, and the LF:HF ratio, with HF ( p < 0.001) and LF:HF ratio during the stress task with medical students having a narrower increase in HRV parameters than the general population.…”

Smart Homes as Enablers for Depression Pre-Diagnosis Using PHQ-9 on HMI through Fuzzy Logic Decision System

“…However, this proposal has its limitation regarding which type of user could interact, for instance, with the HMI [ 5 , 7 , 8 ]. Consequently, research suggests that certain personality traits are open to using new gadgets or new technology as the openness or extraversion personality trait.…”

“…Smartphones or wearables, like smartwatches, are often used by single individuals as an extension of their life; they are devices that can help detect and monitor depressive symptoms [ 5 , 7 , 8 ]. On the other hand, smart homes have been arising due to the Internet of Things; for instance, modern household appliances have increased the comfort level of householders [ 9 , 10 , 11 , 12 ].…”