Evaluation of four sensor locations for physical activity assessment

Schall, Mark C.; Fethke, Nathan B.; Chen, Howard

doi:10.1016/j.apergo.2015.09.007

Cited by 25 publications

(15 citation statements)

References 81 publications

(86 reference statements)

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“…For example, many scientists have used accelerometers for behavior monitoring in diverse segments of the body including the hip, wrist, chest, ankle [ 30 , 31 , 32 ]. However, they could not find the best placement for the installation of wearable devices to accurately monitor all activities of daily life [ 33 , 34 ].…”

Section: Methodsmentioning

confidence: 99%

Trunk Motion System (TMS) Using Printed Body Worn Sensor (BWS) via Data Fusion Approach

Esfahani

Zobeiri

Moshiri

et al. 2017

Sensors

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Human movement analysis is an important part of biomechanics and rehabilitation, for which many measurement systems are introduced. Among these, wearable devices have substantial biomedical applications, primarily since they can be implemented both in indoor and outdoor applications. In this study, a Trunk Motion System (TMS) using printed Body-Worn Sensors (BWS) is designed and developed. TMS can measure three-dimensional (3D) trunk motions, is lightweight, and is a portable and non-invasive system. After the recognition of sensor locations, twelve BWSs were printed on stretchable clothing with the purpose of measuring the 3D trunk movements. To integrate BWSs data, a neural network data fusion algorithm was used. The outcome of this algorithm along with the actual 3D anatomical movements (obtained by Qualisys system) were used to calibrate the TMS. Three healthy participants with different physical characteristics participated in the calibration tests. Seven different tasks (each repeated three times) were performed, involving five planar, and two multiplanar movements. Results showed that the accuracy of TMS system was less than 1.0°, 0.8°, 0.6°, 0.8°, 0.9°, and 1.3° for flexion/extension, left/right lateral bending, left/right axial rotation, and multi-planar motions, respectively. In addition, the accuracy of TMS for the identified movement was less than 2.7°. TMS, developed to monitor and measure the trunk orientations, can have diverse applications in clinical, biomechanical, and ergonomic studies to prevent musculoskeletal injuries, and to determine the impact of interventions.

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Section: Methodsmentioning

confidence: 99%

Trunk Motion System (TMS) Using Printed Body Worn Sensor (BWS) via Data Fusion Approach

Esfahani

Zobeiri

Moshiri

et al. 2017

Sensors

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“…Another study reported that nurses spent their working time with different intensities of physical activity, ranging from light-intensity physical activities, standing, or slow walking to moderate-intensity physical activities, turning the patient without assistance, or showering a patient 33) . Although nurses spent only 7% of their time across a 12-h shift engaged in moderate-intensity physical activity 34) , it is possible that completing light-intensity tasks across a long duration can elicit a higher energy expenditure than that by moderate-intensity tasks, due to a lack of recovery time between shifts or tasks 35) . These factors may contribute to an increased risk of plantar fasciitis in nurses.…”

Section: Discussionmentioning

confidence: 99%

Plantar fasciitis in physicians and nurses: a nationwide population-based study

et al. 2020

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Approval of the research protocol This study was strictly conducted according to the Declaration of Helsinki and approved by the Institutional Review Board at Chi-Mei Medical Center. Informed Consent Since the NHIRD contains de-identified information, informed consents from the participants are waived, which does not affect the rights and welfare of the participants. Registry and the Registration No. of the study/Trial N/A.

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“…A second top choice for accelerometry-based devices is the non-dominant wrist [ 69 ], despite the fact that this positioning may not be appropriate for wearers using assistive devices [ 4 ]. Similarly, the placement of IMUs is also debatable, since the accuracy of physical activity measurements using IMUs differs for various sensor positions [ 70 ]. While prior studies have facilitated a greater understanding of the potential for and shortcomings of activity-monitoring systems, none, to the best of our knowledge, have distinguished between intrinsic and extrinsic wearable sensors, and most appear to have focused on the latter.…”

Section: Discussionmentioning

confidence: 99%

Preferred Placement and Usability of a Smart Textile System vs. Inertial Measurement Units for Activity Monitoring

Esfahani

Nussbaum

2018

Sensors

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Wearable sensors and systems have become increasingly popular in recent years. Two prominent wearable technologies for human activity monitoring are smart textile systems (STSs) and inertial measurement units (IMUs). Despite ongoing advances in both, the usability aspects of these devices require further investigation, especially to facilitate future use. In this study, 18 participants evaluate the preferred placement and usability of two STSs, along with a comparison to a commercial IMU system. These evaluations are completed after participants engaged in a range of activities (e.g., sitting, standing, walking, and running), during which they wear two representatives of smart textile systems: (1) a custom smart undershirt (SUS) and commercial smart socks; and (2) a commercial whole-body IMU system. We first analyze responses regarding the usability of the STS, and subsequently compared these results to those for the IMU system. Participants identify a short-sleeved shirt as their preferred activity monitor. In additional, the SUS in combination with the smart socks is rated superior to the IMU system in several aspects of usability. As reported herein, STSs show promise for future applications in human activity monitoring in terms of usability.

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Evaluation of four sensor locations for physical activity assessment

Cited by 25 publications

References 81 publications

Trunk Motion System (TMS) Using Printed Body Worn Sensor (BWS) via Data Fusion Approach

Trunk Motion System (TMS) Using Printed Body Worn Sensor (BWS) via Data Fusion Approach

Plantar fasciitis in physicians and nurses: a nationwide population-based study

Preferred Placement and Usability of a Smart Textile System vs. Inertial Measurement Units for Activity Monitoring

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