A Review of Wrist-Worn Wearable: Sensors, Models, and Challenges

Table 1

Wearable computing review studies.

Study	Domain	Number of reviewed studies	Objectives and outcomes
2015 [38]	Health (rehabilitation and impairment)	Not available (N/A)	(i) The review found that wearable haptic devices are implemented for different clinical applications including rehabilitation, prosthetics, vestibular loss, osteoarthritis, vision loss, and hearing loss.; (ii) Need development of haptic wearables based on clinical needs, multimodal haptic displays, low battery requirements, and long-term usage.
2015 [39]	General health	N/A	(i) Review of recent developments and applications of low-power technologies in wearable telecare and telehealth systems; divided different approaches into hardware-based approaches and firmware-based approaches.; (ii) Need first to realize these systems in the wild, and then increase power efficiency.; (iii) Low-power technologies will benefit people’s daily lives.
2015 [40]	General health	N/A	(i) It discusses opportunities and challenges of wearable applications of health care and behavior changes particularly.
2015 [41]	General health	N/A	(i) Overview of current methods used within wearable applications to monitor and support positive health and wellbeing within an individual.; (ii) Highlight issues and challenges outlined by previous studies and describe the future focuses of work.
2015 [42]	Activity	N/A	(i) Need to develop lightweight physiological sensors to have comfortable wearable devices that enable monitoring of different ranges of activities of inhabitants.
2015 [43]	Activity tracker	22	(i) A systematic review of 22 studies to evaluate validity and reliability of popular consumer wearable activity trackers (Fitbit and Jawbone).; (ii) Determine trackers’ ability to predict steps, distance, physical activity, energy expenditure, and sleep.; (iii) Results: higher validity of steps, few studies on distance and physical activity, and lower validity for energy expenditure and sleep. High interdevice reliability for steps, distance, energy expenditure, and sleep for certain Fitbit models.
2016 [44]	General	793 historical and 103 current	(i) Two-phase survey of the application space of wearable technology by assessing its applications observed in research or industrial activities within two time periods: (a) Historical (up to 2014); (b) Current (2014-2015); (ii) Explore and assess product types, application categories, and the availability of wearable application at the body surface.; (iii) Consider the differences in product price and gender.; (iv) Discuss the effects of changes between the two time periods.; (v) Wrist-worn devices that stand out from the current trends.
2016 [15]	Elderly people	133	(i) Explore frameworks and sensor systems of AALS relative to care and clinical systems.; (ii) Most systems focused on activity monitoring for helping instance risks only.; (iii) Lack of long-term care systems that must add the environmental factors for analytics and decision-making.; (iv) Need to further explore the distributed storage and access to wearable devices and sensors.; (v) Take account of social issues: acceptability and usability.; (vi) Need to consider privacy and cybersecurity issues.
2016 [45]	Health (Parkinson’s disease)	113	(i) Use accelerometer and gyroscope data.; (ii) Improvement of battery life, movement sensors, and information technology to create a long-use clinical device.
2016 [46]	Education	N/A	(i) Require more research to know the needs of wearable technology for education.
2016 [47]	Biometric recognition	N/A	(i) Review and give a categorization of wearable sensors useful for capturing biometric signals.; (ii) Computational cost of the different signal processing techniques.; (iii) Review and classify the recent studies in the field of wearable biometrics.
2017 [48]	Wearable haptic	N/A	(i) Review the wearable haptic systems for only fingertip and hand.; (ii) Summarize the main characteristics of these systems and discuss the main challenges in developments.
2018 [49]	Elderly people	13	(i) Provide a framework for fall detection assessment system that focuses on three factors: sensor placement, task and feature category.; (ii) Summarize the trends of wearable inertial sensors features and provide statistical analysis and meta-analysis for these features.