The usefulness and actual use of wearable devices among the elderly population

Kekade, Shwetambara; Hseieh, Chung-Ho; Islam, Mohaimenul; Atique, Suleman; Khalfan, Abdulwahed Mohammed; Li, Yu-Chuan; Abdul, Shabbir Syed

doi:10.1016/j.cmpb.2017.10.008

Cited by 169 publications

(147 citation statements)

References 34 publications

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“…Inspired by Kekade et al's review from 2018 [2], we conducted a qualitative synthesis of the 73 included research articles. They were published between 2010 and 2019, i.e., spanning approx.…”

Section: Qualitative Synthesismentioning

confidence: 99%

“…Sixty research articles reported on studies conducted with people at some level, these are reported in Table 2. We categorized the sensors according to the sensor categories used in [2], namely, physical activity, vital signs, electrocardiography (ECG) and other. Studies reporting on devices measuring movement or activity were classified under the sensor category physical activity.…”

Section: Qualitative Synthesismentioning

confidence: 99%

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A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

Kristoffersson

Lindén

2020

Sensors

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The use of wearable body sensors for health monitoring is a quickly growing field with the potential of offering a reliable means for clinical and remote health management. This includes both real-time monitoring and health trend monitoring with the aim to detect/predict health deterioration and also to act as a prevention tool. The aim of this systematic review was to provide a qualitative synthesis of studies using wearable body sensors for health monitoring. The synthesis and analysis have pointed out a number of shortcomings in prior research. Major shortcomings are demonstrated by the majority of the studies adopting an observational research design, too small sample sizes, poorly presented, and/or non-representative participant demographics (i.e., age, gender, patient/healthy). These aspects need to be considered in future research work.

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Section: Qualitative Synthesismentioning

confidence: 99%

Section: Qualitative Synthesismentioning

confidence: 99%

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

Kristoffersson

Lindén

2020

Sensors

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“…In the last decade, the consumer market opened the way for a broader acceptance and use of wearable sensing devices. Activity trackers are now widely employed in everyday life, but with limited reliability and validation of results [11,106]. More accurate wearable inertial sensors have been adopted for a wide range of clinical applications [2,107], with a huge potential to innovate and improve nearly every aspect of healthcare applications.…”

Section: Discussionmentioning

confidence: 99%

Kinect and wearable inertial sensors for motor rehabilitation programs at home: state of the art and an experimental comparison

2020

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“…10,11 Great progress has been made in the field of intelligent care. [12][13][14][15][16][17][18][19][20][21] Yao et al 17 developed a low-cost interrogation system that was able to dynamically interrogate the antenna sensor and wirelessly transmit the acquired data to a smart device. Sundaravadivel et al 18 introduced a piezo-electric-based accelerometer sensor design which helped in tracking the physical activities of family and friends.…”

Section: Introductionmentioning

confidence: 99%

Intelligent health monitoring system based on smart clothing

Lin

Yang

Zhou

et al. 2018

International Journal of Distributed Sensor Networks

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In this study, we proposed an intelligent health monitoring system based on smart clothing. The system consisted of smart clothing and sensing component, care institution control platform, and mobile device. The smart clothing is a wearable device for electrocardiography signal collection and heart rate monitoring. The system integrated our proposed fast empirical mode decomposition algorithm for electrocardiography denoising and hidden Markov model-based algorithm for fall detection. Eight kinds of services were provided by the system, including surveillance of signs of life, tracking of physiological functions, monitoring of the activity field, anti-lost, fall detection, emergency call for help, device wearing detection, and device low battery warning. The performance of fast empirical mode decomposition and hidden Markov model were evaluated by experiment I (fast empirical mode decomposition evaluation) and experiment II (fall detection), respectively. The accuracy and sensitivity of R-peak detection using fast empirical mode decomposition were 96.46% and 98.75%, respectively. The accuracy, sensitivity, and specificity of fall detection using hidden Markov model were 97.92%, 90.00%, and 99.50%, respectively. The system was evaluated in an elderly long-term care institution in Taiwan. The results of the satisfaction survey showed that both the caregivers and the elders are willing to use the proposed intelligent health monitoring system. The proposed system may be used for long-term health monitoring.

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The usefulness and actual use of wearable devices among the elderly population

Cited by 169 publications

References 34 publications

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

Kinect and wearable inertial sensors for motor rehabilitation programs at home: state of the art and an experimental comparison

Intelligent health monitoring system based on smart clothing

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