scholarly journals It’s not about the capture, it’s about what we can learn”: a qualitative study of experts’ opinions and experiences regarding the use of wearable sensors to measure gait and physical activity

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Alison Keogh ◽  
Kristin Taraldsen ◽  
Brian Caulfield ◽  
Beatrix Vereijken
Keyword(s):  
Physical Activity ◽  
Clinical Practice ◽  
Paradigm Shift ◽  
Wearable Sensors ◽  
Wearable Devices ◽  
Healthcare Research ◽  
Quality Data ◽  
Sensor Technology ◽  
Wearable Sensor ◽  
Structured Interviews

Abstract Background The use of wearable sensor technology to collect patient health data, such as gait and physical activity, offers the potential to transform healthcare research. To maximise the use of wearable devices in practice, it is important that they are usable by, and offer value to, all stakeholders. Although previous research has explored participants’ opinions of devices, to date, limited studies have explored the experiences and opinions of the researchers who use and implement them. Researchers offer a unique insight into wearable devices as they may have access to multiple devices and cohorts, and thus gain a thorough understanding as to how and where this area needs to progress. Therefore, the aim of this study was to explore the experiences and opinions of researchers from academic, industry and clinical contexts, in the use of wearable devices to measure gait and physical activity. Methods Twenty professionals with experience using wearable devices in research were recruited from academic, industry and clinical backgrounds. Independent, semi-structured interviews were conducted, audio-recorded and transcribed. Transcribed texts were analysed using inductive thematic analysis. Results Five themes were identified: (1) The positives and negatives of using wearable devices in research, (2) The routine implementation of wearable devices into research and clinical practice, (3) The importance of compromise in protocols, (4) Securing good quality data, and (5) A paradigm shift. Researchers overwhelmingly supported the use of wearable sensor technology due to the insights that they may provide. Though barriers remain, researchers were pragmatic towards these, believing that there is a paradigm shift happening in this area of research that ultimately requires mistakes and significant volumes of further research to allow it to progress. Conclusions Multiple barriers to the use of wearable devices in research and clinical practice remain, including data management and clear clinical utility. However, researchers strongly believe that the potential benefit of these devices to support and create new clinical insights for patient care, is greater than any current barrier. Multi-disciplinary research integrating the expertise of both academia, industry and clinicians is a fundamental necessity to further develop wearable devices and protocols that match the varied needs of all stakeholders.

scholarly journals Sociometric wearable devices for studying human behavior in corporate and healthcare workplaces

BioTechniques ◽  
2021 ◽  
Author(s):  
Asami Ito-Masui ◽  
Eiji Kawamoto ◽  
Ryo Esumi ◽  
Hiroshi Imai ◽  
Motomu Shimaoka
Keyword(s):  
Wearable Sensors ◽  
Wearable Devices ◽  
Healthcare Research ◽  
Human Interaction ◽  
Sensor Technology ◽  
Wearable Sensor ◽  
Social Constructs ◽  
Medical Settings ◽  
Human Interactions ◽  
Study Designs

Wearable sensor technology enables objective data collection of direct human interactions. The authors review sociometric wearable devices (SWD) and their application in healthcare. Human interactions captured by wearable sensors have been shown to correlate with social constructs such as teamwork and productivity in the office. Application of SWD in the field of healthcare requires special considerations: validation studies have shown technological disadvantages in acute medical settings. Application of SWD in healthcare should be considered based on the strengths and weaknesses of the methodology. SWD can also play an important role in investigation of human interaction and epidemic spread. When study designs and methodologies are carefully considered, incorporation of SWD in healthcare research has promising potential for new insights.

scholarly journals Recommendations for Assessment of the Reliability, Sensitivity, and Validity of Data Provided by Wearable Sensors Designed for Monitoring Physical Activity (Preprint)

2017 ◽  
Author(s):  
Peter Düking ◽  
Franz Konstantin Fuss ◽  
Hans-Christer Holmberg ◽  
Billy Sperlich
Keyword(s):  
Physical Activity ◽  
Wearable Sensors ◽  
Wearable Devices ◽  
Insurance Companies ◽  
Sensor Technology ◽  
Wearable Sensor ◽  
Scientific Evaluation ◽  
Reliability Sensitivity ◽  
The Individual ◽  
Recommendations For Assessment

UNSTRUCTURED Although it is becoming increasingly popular to monitor parameters related to training, recovery, and health with wearable sensor technology (wearables), scientific evaluation of the reliability, sensitivity, and validity of such data is limited and, where available, has involved a wide variety of approaches. To improve the trustworthiness of data collected by wearables and facilitate comparisons, we have outlined recommendations for standardized evaluation. We discuss the wearable devices themselves, as well as experimental and statistical considerations. Adherence to these recommendations should be beneficial not only for the individual, but also for regulatory organizations and insurance companies.

scholarly journals Patient perspectives of wearable sensors: a mixed methods evaluation (Preprint)

2020 ◽  
Author(s):  
Meera Joshi ◽  
Stephanie Archer ◽  
Abigail Morbi ◽  
Sonal Arora ◽  
Richard Kwasnicki ◽  
...  
Keyword(s):  
Wearable Sensors ◽  
Surgical Patients ◽  
Sensor Technology ◽  
Patient Questionnaire ◽  
Continuous Variables ◽  
Wearable Sensor ◽  
Structured Interviews ◽  
Patient Deterioration ◽  
Mixed Methods Evaluation ◽  
Interview Studies

BACKGROUND Continuous vital sign monitoring using wearable sensors may enable earlier detection of patient deterioration and sepsis. OBJECTIVE To explore patient experiences of wearable sensor technology and continuous monitoring through questionnaire and interview studies. METHODS All patients recruited for a wearable sensor study were asked to complete a study questionnaire. Patients were asked 9 questions with answers on Likert scale and scores were treated as continuous variables. A subgroup of surgical patients wearing the wearable sensor were invited to take part in semi-structured interviews. All interview data was analysed using thematic analysis. RESULTS A total of 453 patients completed the patient questionnaire (90.6% response rate). A high proportion of patients agreed the wearable sensor was comfortable to wear (n=427, 85.4%), they would wear the patch again when in hospital (n=429, 85.8%) and they would wear the wearable patch at home (n=398, 79.6%). Twelve surgical patients consented to interviews. Five main themes of interest to patients emerged from the interviews; 1) Centralised monitoring 2) enhanced feelings of patient safety, 3) impact on nursing staff 4) comfort & usability and 5) the future and views on technology. CONCLUSIONS Overall, the feedback from patients using wearable monitoring was strongly positive with relatively few concerns raised. Patients feel wearable sensors improve their sense of safety, may relieve pressure on healthcare staff and are a welcome part of future healthcare

Accuracy of Wearable Sensor Technology in Hand Goniometry: A Systematic Review

Hand ◽  
2021 ◽  
pp. 155894472110146
Author(s):  
Francisco R. Avila ◽  
Rickey E. Carter ◽  
Christopher J. McLeod ◽  
Charles J. Bruce ◽  
Davide Giardi ◽  
...  
Keyword(s):  
Systematic Review ◽  
Range Of Motion ◽  
Health Care Professionals ◽  
Inertial Sensors ◽  
Measurement Techniques ◽  
Infrared Camera ◽  
Wearable Devices ◽  
Sensor Technology ◽  
Accuracy Evaluation ◽  
Wearable Sensor

Background Wearable devices and sensor technology provide objective, unbiased range of motion measurements that help health care professionals overcome the hindrances of protractor-based goniometry. This review aims to analyze the accuracy of existing wearable sensor technologies for hand range of motion measurement and identify the most accurate one. Methods We performed a systematic review by searching PubMed, CINAHL, and Embase for studies evaluating wearable sensor technology in hand range of motion assessment. Keywords used for the inquiry were related to wearable devices and hand goniometry. Results Of the 71 studies, 11 met the inclusion criteria. Ten studies evaluated gloves and 1 evaluated a wristband. The most common types of sensors used were bend sensors, followed by inertial sensors, Hall effect sensors, and magnetometers. Most studies compared wearable devices with manual goniometry, achieving optimal accuracy. Although most of the devices reached adequate levels of measurement error, accuracy evaluation in the reviewed studies might be subject to bias owing to the use of poorly reliable measurement techniques for comparison of the devices. Conclusion Gloves using inertial sensors were the most accurate. Future studies should use different comparison techniques, such as infrared camera–based goniometry or virtual motion tracking, to evaluate the performance of wearable devices.

The Feasibility and Effectiveness of Wearable Sensor Technology in the Management of Elderly Diabetics with Foot Ulcer Remission: A Proof-Of-Concept Pilot Study with Six Cases

Gerontology ◽  
2021 ◽  
pp. 1-10
Author(s):  
Chenzhen Du ◽  
Hongyan Wang ◽  
Heming Chen ◽  
Xiaoyun Fan ◽  
Dongliang Liu ◽  
...  
Keyword(s):  
Odds Ratio ◽  
Stride Length ◽  
Wearable Sensors ◽  
Foot Ulcer ◽  
Wearable Devices ◽  
Foot Ulcers ◽  
Diabetic Patients ◽  
Wearable Sensor ◽  
Double Support ◽  
Gait Parameters

Aims: Using specials wearable sensors, we explored changes in gait and balance parameters, over time, in elderly patients at high risk of diabetic foot, wearing different types of footwear. This assessed the relationship between gait and balance changes in elderly diabetic patients and the development of foot ulcers, in a bid to uncover potential benefits of wearable devices in the prognosis and management of the aforementioned complication. Methods: A wearable sensor-based monitoring system was used in middle-elderly patients with diabetes who recently recovered from neuropathic plantar foot ulcers. A total of 6 patients (age range: 55–80 years) were divided into 2 groups: the therapeutic footwear group (n = 3) and the regular footwear (n = 3) group. All subjects were assessed for gait and balance throughout the study period. Walking ability and gait pattern were assessed by allowing participants to walk normally for 1 min at habitual speed. The balance assessment program incorporated the “feet together” standing test and the instrumented modified Clinical Test of Sensory Integration and Balance. Biomechanical information was monitored at least 3 times. Results: We found significant differences in stride length (p < 0.0001), stride velocity (p < 0.0001), and double support (p < 0.0001) between the offloading footwear group (OG) and the regular footwear group on a group × time interaction. The balance test embracing eyes-open condition revealed a significant difference in Hip Sway (p = 0.004), COM Range ML (p = 0.008), and COM Position (p = 0.004) between the 2 groups. Longitudinally, the offloading group exhibited slight improvement in the performance of gait parameters over time. The stride length (odds ratio 3.54, 95% CI 1.34–9.34, p = 0.018) and velocity (odds ratio 3.13, 95% CI 1.19–8.19, p = 0.033) of OG patients increased, converse to the double-support period (odds ratio 6.20, 95% CI 1.97–19.55, p = 0.002), which decreased. Conclusions: Special wearable devices can accurately monitor gait and balance parameters in patients in real time. The finding reveals the feasibility and effectiveness of advanced wearable sensors in the prevention and management of diabetic foot ulcer and provides a solid background for future research. In addition, the development of foot ulcers in elderly diabetic patients may be associated with changes in gait parameters and the nature of footwear. Even so, larger follow-up studies are needed to validate our findings.

scholarly journals Acceptability of Continuous Glucose Monitoring in Free-Living Healthy Individuals: Implications for the Use of Wearable Biosensors in Diet and Physical Activity Research (Preprint)

2018 ◽  
Author(s):  
Yue Liao ◽  
Susan Schembre
Keyword(s):  
Physical Activity ◽  
Wearable Sensors ◽  
Glucose Monitoring ◽  
Relevant Information ◽  
Sensor Technology ◽  
Physiological Data ◽  
Clinical Settings ◽  
Continuous Glucose Monitor ◽  
Diet And Physical Activity ◽  
Study Participants

BACKGROUND Wearable sensors have been increasingly used in behavioral research for real-time assessment and intervention purposes. The rapid advancement of biomedical technology typically used in clinical settings has made wearable sensors more accessible to a wider population. Yet the acceptability of this technology for nonclinical purposes has not been examined. OBJECTIVE The aim was to assess the acceptability of wearing a continuous glucose monitor (CGM) device among a sample of nondiabetic individuals, and to compare the acceptability of a CGM between a mobile diet tracking app (MyFitnessPal) and an accelerometer. METHODS A total of 30 nondiabetic adults went through a 7-day observational study. They wore a CGM sensor, tracked their diet and physical activity using the CGM receiver and MyFitnessPal, and wore an accelerometer on their waist. After the monitoring period, they completed a 10-item survey regarding acceptability of each of the study tools. Two-tailed paired-sample t tests were conducted to examine whether the summary acceptability scores were comparable between the CGM sensor/receiver and MyFitnessPal/accelerometer. RESULTS More than 90% of the study participants agreed that the CGM sensor and receiver were easy to use (28/30 and 27/30, respectively), useful (28/30 and 29/30, respectively), and provided relevant information that was of interest to them (27/30 and 28/30, respectively). The summary acceptability scores (out of a 5-point Likert scale) were mean 4.06 (SD 0.55) for the CGM sensor, mean 4.05 (SD 0.58) for the CGM receiver, mean 4.10 (SD 0.68) for MyFitnessPal, and mean 3.73 (SD 0.76) for the accelerometer. CONCLUSIONS The high acceptability of using a CGM from this study suggests a great potential for using CGMs in nondiabetic adults in research settings. Although potential selection bias might contribute to the high acceptability in this study, the continued advancements in wearable sensor technology will make the barriers to tracking and collecting personal physiological data more and more minimal.

scholarly journals A review of wearable sensors based monitoring with daily physical activity to manage type 2 diabetes

2021 ◽  
Vol 11 (1) ◽  
pp. 646 ◽  
Author(s):  
Omar AlShorman ◽  
Buthaynah Alshorman ◽  
Fahed Alkahtani
Keyword(s):  
Physical Activity ◽  
Wearable Sensors ◽  
Wearable Devices ◽  
Vital Role ◽  
Daily Physical Activity ◽  
Daily Monitoring ◽  
Glucose Levels ◽  
Type Two Diabetes

Globally, the aging and the lifestyle lead to rabidly increment of the number of type two diabetes (T2D) patients. Critically, T2D considers as one of the most challenging healthcare issue. Importantly, physical activity (PA) plays a vital role of improving glycemic control T2D. However, daily monitoring of T2D using wearable devices/ sensors have a crucial role to monitor glucose levels in the blood. Nowadays, daily physical activity (PA) and exercises have been used to manage T2D. The main contribution of the proposed study is to review the literature about managing and monitoring T2D with daily PA through wearable devices and sensors. Finally, challenges and future trends are also highlighted.

scholarly journals The Use of Wearable Sensor Technology to Detect Shock Impacts in Sports and Occupational Settings: A Scoping Review

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 4962
Author(s):  
Ingrid Eitzen ◽  
Julie Renberg ◽  
Hilde Færevik
Keyword(s):  
Scoping Review ◽  
Wearable Sensors ◽  
Real Life ◽  
Team Sports ◽  
Sensor Technology ◽  
Wearable Sensor ◽  
Dominant Type ◽  
Inner Organs ◽  
Shock Impacts ◽  
Occupational Settings

Shock impacts during activity may cause damage to the joints, muscles, bones, or inner organs. To define thresholds for tolerable impacts, there is a need for methods that can accurately monitor shock impacts in real-life settings. Therefore, the main aim of this scoping review was to present an overview of existing methods for assessments of shock impacts using wearable sensor technology within two domains: sports and occupational settings. Online databases were used to identify papers published in 2010–2020, from which we selected 34 papers that used wearable sensor technology to measure shock impacts. No studies were found on occupational settings. For the sports domain, accelerometry was the dominant type of wearable sensor technology utilized, interpreting peak acceleration as a proxy for impact. Of the included studies, 28 assessed foot strike in running, head impacts in invasion and team sports, or different forms of jump landings or plyometric movements. The included studies revealed a lack of consensus regarding sensor placement and interpretation of the results. Furthermore, the identified high proportion of validation studies support previous concerns that wearable sensors at present are inadequate as a stand-alone method for valid and accurate data on shock impacts in the field.

scholarly journals A Combination of Indoor Localization and Wearable Sensor–Based Physical Activity Recognition to Assess Older Patients Undergoing Subacute Rehabilitation: Baseline Study Results (Preprint)

2019 ◽  
Author(s):  
Ramin Ramezani ◽  
Wenhao Zhang ◽  
Zhuoer Xie ◽  
John Shen ◽  
David Elashoff ◽  
...  
Keyword(s):  
Physical Activity ◽  
Health Care ◽  
Activity Recognition ◽  
Human Activity ◽  
Random Forests ◽  
Energy Intensity ◽  
Indoor Localization ◽  
Low Cost ◽  
Wearable Sensors ◽  
Wearable Devices

BACKGROUND Health care, in recent years, has made great leaps in integrating wireless technology into traditional models of care. The availability of ubiquitous devices such as wearable sensors has enabled researchers to collect voluminous datasets and harness them in a wide range of health care topics. One of the goals of using on-body wearable sensors has been to study and analyze human activity and functional patterns, thereby predicting harmful outcomes such as falls. It can also be used to track precise individual movements to form personalized behavioral patterns, to standardize the concept of frailty, well-being/independence, etc. Most wearable devices such as activity trackers and smartwatches are equipped with low-cost embedded sensors that can provide users with health statistics. In addition to wearable devices, Bluetooth low-energy sensors known as BLE beacons have gained traction among researchers in ambient intelligence domain. The low cost and durability of newer versions have made BLE beacons feasible gadgets to yield indoor localization data, an adjunct feature in human activity recognition. In the studies by Moatamed et al and the patent application by Ramezani et al, we introduced a generic framework (Sensing At-Risk Population) that draws on the classification of human movements using a 3-axial accelerometer and extracting indoor localization using BLE beacons, in concert. OBJECTIVE The study aimed to examine the ability of combination of physical activity and indoor location features, extracted at baseline, on a cohort of 154 rehabilitation-dwelling patients to discriminate between subacute care patients who are re-admitted to the hospital versus the patients who are able to stay in a community setting. METHODS We analyzed physical activity sensor features to assess activity time and intensity. We also analyzed activities with regard to indoor localization. Chi-square and Kruskal-Wallis tests were used to compare demographic variables and sensor feature variables in outcome groups. Random forests were used to build predictive models based on the most significant features. RESULTS Standing time percentage (P<.001, d=1.51), laying down time percentage (P<.001, d=1.35), resident room energy intensity (P<.001, d=1.25), resident bed energy intensity (P<.001, d=1.23), and energy percentage of active state (P=.001, d=1.24) are the 5 most statistically significant features in distinguishing outcome groups at baseline. The energy intensity of the resident room (P<.001, d=1.25) was achieved by capturing indoor localization information. Random forests revealed that the energy intensity of the resident room, as a standalone attribute, is the most sensitive parameter in the identification of outcome groups (area under the curve=0.84). CONCLUSIONS This study demonstrates that a combination of indoor localization and physical activity tracking produces a series of features at baseline, a subset of which can better distinguish between at-risk patients that can gain independence versus the patients that are rehospitalized.

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