2020
DOI: 10.3390/s20051502
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A Systematic Review on the Use of Wearable Body Sensors for Health Monitoring: A Qualitative Synthesis

Abstract: 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 num… Show more

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Cited by 49 publications
(72 citation statements)
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References 83 publications
(140 reference statements)
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“…An emerging way to assess mobility performance is using Digital Mobility Outcomes (DMOs), which are mobility outcomes that are obtained by processing the recordings of wearable IMU, in order to extract specific features of the individual walking dynamics. Unfortunately, the first generation of these technologies was primarily designed for the consumer market as a motivational tool for young, healthy, fit and physically active adults [ 28 , 29 , 30 , 31 ]. When used as measurement tools, many of these sensors are very inaccurate [ 32 , 33 ], and even the most accurate become unreliable when used to monitor mobility performance in patients with some degree of mobility disability, particularly when walking at very slow speeds [ 34 , 35 ].…”
Section: Introductionmentioning
confidence: 99%
“…An emerging way to assess mobility performance is using Digital Mobility Outcomes (DMOs), which are mobility outcomes that are obtained by processing the recordings of wearable IMU, in order to extract specific features of the individual walking dynamics. Unfortunately, the first generation of these technologies was primarily designed for the consumer market as a motivational tool for young, healthy, fit and physically active adults [ 28 , 29 , 30 , 31 ]. When used as measurement tools, many of these sensors are very inaccurate [ 32 , 33 ], and even the most accurate become unreliable when used to monitor mobility performance in patients with some degree of mobility disability, particularly when walking at very slow speeds [ 34 , 35 ].…”
Section: Introductionmentioning
confidence: 99%
“…Ten articles [4], [12], [18], [29], [30], [31], [32], [33], [34] and [35] dealt with interventions that could be clearly classi ed as falling into the preventive, pre-clinical or hospital, emergency and-/or primary care settings. The majority of the above articles, except [30], [31] and [34] combined the above setting with other settings such as the hospital or post-hospital monitoring.…”
Section: Rpmts Positioning In the Healthcare Landscapementioning
confidence: 99%
“…reviews [8], [9], [11], [30], [33], [34], [50] and [51] out of 26, targeted only one disease such as diabetes, COPD, or asthma, and 3 reviews [8], [30] and [33] discussed interventions related to cardiovascular diseases. The remaining 5 reviews did not provide su cient details to determine whether they targeted one or more diseases.…”
Section: Functional Versatility (Number and Nature Of Targeted Diseases)mentioning
confidence: 99%
“…In these situations, the momentary monitoring of patients helps the medical team to take the necessary measures without delay. Patient monitoring announces the threatening events to caretakers, and most of such systems use the physiological input data for the direct control of support tools (Baskar et al 2020 ; Kristoffersson and Lindén 2020 ). Anyhow, considering the present global conditions, the smart wearable sensors for patients̓ s monitoring have the capacity and potential to be a major breakthrough in efforts to control the epidemics.…”
Section: Introductionmentioning
confidence: 99%
“…Over the years, many outbreaks of infectious diseases have occurred and spread across the world (Kristoffersson and Lindén 2020 ). According to the points which were mentioned above, the way of public health surveillance could enlighten by using wearable device data.…”
Section: Introductionmentioning
confidence: 99%