Mobile and wearable technologies in healthcare for the ageing population

Malwade, Shwetambara; Abdul, Shabbir Syed; Uddin, Mohy; Nursetyo, Aldilas Achmad; Fernández-Luque, Luis; Zhu, Xinxin; Cilliers, Liezel; Wong, Chun-Por; Bamidis, Panagiotis D.; Li, Yu-Chuan

doi:10.1016/j.cmpb.2018.04.026

Cited by 107 publications

(65 citation statements)

References 44 publications

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“…However, all the studies mentioned above were conducted on young or middle-aged adults, mostly in good health. Considering the multiple applications of wrist-based technology and the potential adoption in healthcare, and cognizant of an aging population, it is important to investigate the use of these devices in different populations, such as older people [28]. Research has explored the acceptability of commercial trackers to older adults [29–30], showing the current barriers to acceptability and the limitations of the available devices (in terms of data accessibility, ease-of-use, and wearability being impacted by the effects of ageing on skin, such as wrinkling and dryness of the skin, and so on), and defining the features that future older population-oriented trackers should provide to address acceptability issues [30].…”

Section: Introductionmentioning

confidence: 99%

Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults

et al. 2019

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Wrist-worn activity trackers have experienced a tremendous growth lately and studies on the accuracy of mainstream trackers used by older adults are needed. This study explores the performance of six trackers (Fitbit Charge2, Garmin VivoSmart HR+, Philips Health Watch, Withings Pulse Ox, ActiGraph GT9X-BT, Omron HJ-72OITC) for estimating: steps, travelled distance, and heart-rate measurements for a cohort of older adults. Eighteen older adults completed a structured protocol involving walking tasks, simulated household activities, and sedentary activities. Less standardized activities were also included, such as: dusting, using a walking aid, or playing cards, in order to simulate real-life scenarios. Wrist-mounted and chest/waist-mounted devices were used. Gold-standards included treadmill, ECG-based chest strap, direct observation or video recording according to the activity and parameter. Every tracker showed a decreasing accuracy with slower walking speed, which resulted in a significant step under-counting. A large mean absolute percentage error (MAPE) was found for every monitor at slower walking speeds with the lowest reported MAPE at 2 km/h being 7.78%, increasing to 20.88% at 1.5 km/h, and 44.53% at 1 km/h. During household activities, the MAPE climbing up/down-stairs ranged from 8.38–19.3% and 10.06–19.01% (dominant and non-dominant arm), respectively. Waist-worn devices showed a more uniform performance. However, unstructured activities (e.g. dusting, playing cards), and using a walking aid represent a challenge for all wrist-worn trackers as evidenced by large MAPE (> 57.66% for dusting, > 67.32% when using a walking aid). Poor performance in travelled distance estimation was also evident during walking at low speeds and climbing up/down-stairs (MAPE > 71.44% and > 48.3%, respectively). Regarding heart-rate measurement, there was no significant difference (p-values > 0.05) in accuracy between trackers placed on the dominant or non-dominant arm. Concordant with existing literature, while the mean error was limited (between -3.57 bpm and 4.21 bpm), a single heart-rate measurement could be underestimated up to 30 beats-per-minute. This study showed a number of limitations of consumer-level wrist-based activity trackers for older adults. Therefore caution is required when used, in healthcare or in research settings, to measure activity in older adults.

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Section: Introductionmentioning

confidence: 99%

Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults

et al. 2019

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“…Important factors in the formation of favorable conditions for the successful implementation of higher education programs are as follows: timely improvement of the education system [5], successful implementation of personnel policy that would satisfy employees and students of HEIs [6,7], improvement of personnel training [8], conflict-free interpersonal relationships [9], teachers' motivation [10], etc. In recent decades, the elements of gamification have been widely used in psychology [11,12], education [13,14], business [15], marketing, social networks [16], health care service [17,18] and in other areas. In marketing practice, gamification is used to influence the behavior of consumers and increase the interest of buyers (consumers) in a particular product or service [19].…”

Section: Introductionmentioning

confidence: 99%

Studentsâ€™ Satisfaction with Interactive Forms of Training with Elements of Gamification

Demchenko¹,

Vinichenko²,

Демченко³

et al. 2018

IJET

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The article considers students' satisfaction with interactive forms of training with elements of gamification. Based on the empirical study, the level of students’ satisfaction with interactive forms of training with elements of gamification has been measured. The study has been conducted at 6 educational organizations that carry out educational activities on educational programs of higher education – bachelor, specialist and master degree programs. A set of sociological methods has been used in the study: a questionnaire survey of students, an expert survey of teachers working at higher education institutions, an analysis of documents; content analysis; a method of mathematical data processing (correlation analysis, using the software package SPSS Statistics 23). Based on the analysis of the scientific literature and the results of the sociological research conducted, it has been established that the students are more satisfied with the quality of interactive sessions with elements of gamification (57.01%) than with the quality of training by traditional methods (23.36%) and the quality of the content of classes conducted by traditional methods (19.63%). It has been revealed that the use of interactive forms of training with elements of gamification is the most effective: to increase the effectiveness of mastering the training material (20%); for decision-making (17.33%); to heighten interest in learning (15.33%). The closeness of the views of students and teachers on the assessment of interactive forms of training with elements of gamification and assessment of classes conducted by traditional methods has been determined by means of Spearman's rank correlation coefficient. The obtained data of the correlation analysis have shown a rather high level of correlation and indicated the closeness of the views of students and teachers on the phenomena studied.

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“…In order to tackle the leading causes of morbidity and mortality that may result from infections to chronic conditions especially in older adults and ageing population, the accessibility and provision of long-term care and palliative care, when and where needed by them, is crucial. With the continuous challenges and rising demands of the elderly, remote and home-based care, the technological innovations in the fields of digital health and health information and communication technologies, such as mobile health, wearable technologies, telemedicine and personalized medicine have transformed the ways of practice and delivery of healthcare in the recent decades [2]. Wearable technologies have been extensively used in the healthcare sector with multi-purpose applications ranging from patient care to personal health.…”

Section: Introductionmentioning

confidence: 99%

Data Analytics and Applications of the Wearable Sensors in Healthcare: An Overview

Uddin

Syed-Abdul

2020

Sensors

Self Cite

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Mobile and wearable technologies in healthcare for the ageing population

Cited by 107 publications

References 44 publications

Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults

Accuracy of consumer-level and research-grade activity trackers in ambulatory settings in older adults

Studentsâ€™ Satisfaction with Interactive Forms of Training with Elements of Gamification

Data Analytics and Applications of the Wearable Sensors in Healthcare: An Overview

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