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Giurgiu M, Timm I, Becker M, Schmidt S, Wunsch K, Nissen R, Davidovski D, Bussmann JBJ, Nigg CR, Reichert M, Ebner-Priemer UW, Woll A, von Haaren-Mack B. Quality Evaluation of Free-living Validation Studies for the Assessment of 24-Hour Physical Behavior in Adults via Wearables: Systematic Review. JMIR Mhealth Uhealth 2022; 10:e36377. [PMID: 35679106 PMCID: PMC9227659 DOI: 10.2196/36377] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 04/27/2022] [Accepted: 04/29/2022] [Indexed: 12/13/2022] Open
Abstract
Background Wearable technology is a leading fitness trend in the growing commercial industry and an established method for collecting 24-hour physical behavior data in research studies. High-quality free-living validation studies are required to enable both researchers and consumers to make guided decisions on which study to rely on and which device to use. However, reviews focusing on the quality of free-living validation studies in adults are lacking. Objective This study aimed to raise researchers’ and consumers’ attention to the quality of published validation protocols while aiming to identify and compare specific consistencies or inconsistencies between protocols. We aimed to provide a comprehensive and historical overview of which wearable devices have been validated for which purpose and whether they show promise for use in further studies. Methods Peer-reviewed validation studies from electronic databases, as well as backward and forward citation searches (1970 to July 2021), with the following, required indicators were included: protocol must include real-life conditions, outcome must belong to one dimension of the 24-hour physical behavior construct (intensity, posture or activity type, and biological state), the protocol must include a criterion measure, and study results must be published in English-language journals. The risk of bias was evaluated using the Quality Assessment of Diagnostic Accuracy Studies-2 tool with 9 questions separated into 4 domains (patient selection or study design, index measure, criterion measure, and flow and time). Results Of the 13,285 unique search results, 222 (1.67%) articles were included. Most studies (153/237, 64.6%) validated an intensity measure outcome such as energy expenditure. However, only 19.8% (47/237) validated biological state and 15.6% (37/237) validated posture or activity-type outcomes. Across all studies, 163 different wearables were identified. Of these, 58.9% (96/163) were validated only once. ActiGraph GT3X/GT3X+ (36/163, 22.1%), Fitbit Flex (20/163, 12.3%), and ActivPAL (12/163, 7.4%) were used most often in the included studies. The percentage of participants meeting the quality criteria ranged from 38.8% (92/237) to 92.4% (219/237). On the basis of our classification tree to evaluate the overall study quality, 4.6% (11/237) of studies were classified as low risk. Furthermore, 16% (38/237) of studies were classified as having some concerns, and 72.9% (173/237) of studies were classified as high risk. Conclusions Overall, free-living validation studies of wearables are characterized by low methodological quality, large variability in design, and focus on intensity. Future research should strongly aim at biological state and posture or activity outcomes and strive for standardized protocols embedded in a validation framework. Standardized protocols for free-living validation embedded in a framework are urgently needed to inform and guide stakeholders (eg, manufacturers, scientists, and consumers) in selecting wearables for self-tracking purposes, applying wearables in health studies, and fostering innovation to achieve improved validity.
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Affiliation(s)
- Marco Giurgiu
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Irina Timm
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Marlissa Becker
- Unit Physiotherapy, Department of Orthopedics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Steffen Schmidt
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Kathrin Wunsch
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Rebecca Nissen
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Denis Davidovski
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Johannes B J Bussmann
- Department of Rehabilitation Medicine, Erasmus MC, University Medical Center Rotterdam, Rotterdam, Netherlands
| | - Claudio R Nigg
- Health Science Department, Institute of Sport Science, University of Bern, Bern, Switzerland
| | - Markus Reichert
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.,Department of eHealth and Sports Analytics, Faculty of Sport Science, Ruhr-University Bochum, Bochum, Germany
| | - Ulrich W Ebner-Priemer
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany.,Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Alexander Woll
- Department of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Birte von Haaren-Mack
- Department of Health and Social Psychology, Institute of Psychology, German Sport University, Cologne, Germany
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Kant N, Peters GM, Voorthuis BJ, Groothuis-Oudshoorn CGM, Koning MV, Witteman BPL, Rinia-Feenstra M, Doggen CJM. Continuous vital sign monitoring using a wearable patch sensor in obese patients: a validation study in a clinical setting. J Clin Monit Comput 2021; 36:1449-1459. [PMID: 34878613 DOI: 10.1007/s10877-021-00785-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2021] [Accepted: 11/27/2021] [Indexed: 10/19/2022]
Abstract
Our aim was to determine the agreement of heart rate (HR) and respiratory rate (RR) measurements by the Philips Biosensor with a reference monitor (General Electric Carescape B650) in severely obese patients during and after bariatric surgery. Additionally, sensor reliability was assessed. Ninety-four severely obese patients were monitored with both the Biosensor and reference monitor during and after bariatric surgery. Agreement was defined as the mean absolute difference between both monitoring devices. Bland Altman plots and Clarke Error Grid analysis (CEG) were used to visualise differences. Sensor reliability was reflected by the amount, duration and causes of data loss. The mean absolute difference for HR was 1.26 beats per minute (bpm) (SD 0.84) during surgery and 1.84 bpm (SD 1.22) during recovery, and never exceeded the 8 bpm limit of agreement. The mean absolute difference for RR was 1.78 breaths per minute (brpm) (SD 1.90) during surgery and 4.24 brpm (SD 2.75) during recovery. The Biosensor's RR measurements exceeded the 2 brpm limit of agreement in 58% of the compared measurements. Averaging 15 min of measurements for both devices improved agreement. CEG showed that 99% of averaged RR measurements resulted in adequate treatment. Data loss was limited to 4.5% of the total duration of measurements for RR. No clear causes for data loss were found. The Biosensor is suitable for remote monitoring of HR, but not RR in morbidly obese patients. Future research should focus on improving RR measurements, the interpretation of continuous data, and development of smart alarm systems.
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Affiliation(s)
- Niels Kant
- Department of Anesthesiology and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands
| | - Guido M Peters
- Scientific Bureau, Rijnstate Hospital, Rijnstate Research Center, Wagnerlaan 55, PO Box 9555, 6800 TA, Arnhem, The Netherlands.,Technical Medical Centre, Department of Health Technology and Services Research, University of Twente, Enschede, The Netherlands
| | - Brenda J Voorthuis
- Technical Medical Centre, Department of Health Technology and Services Research, University of Twente, Enschede, The Netherlands
| | | | - Mark V Koning
- Department of Anesthesiology and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands
| | | | - Myra Rinia-Feenstra
- Department of Anesthesiology and Pain Management, Rijnstate Hospital, Arnhem, The Netherlands
| | - Carine J M Doggen
- Scientific Bureau, Rijnstate Hospital, Rijnstate Research Center, Wagnerlaan 55, PO Box 9555, 6800 TA, Arnhem, The Netherlands. .,Technical Medical Centre, Department of Health Technology and Services Research, University of Twente, Enschede, The Netherlands.
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Optimization and Validation of a Classification Algorithm for Assessment of Physical Activity in Hospitalized Patients. SENSORS 2021; 21:s21051652. [PMID: 33673447 PMCID: PMC7956397 DOI: 10.3390/s21051652] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 02/19/2021] [Accepted: 02/22/2021] [Indexed: 11/17/2022]
Abstract
Low amounts of physical activity (PA) and prolonged periods of sedentary activity are common in hospitalized patients. Objective PA monitoring is needed to prevent the negative effects of inactivity, but a suitable algorithm is lacking. The aim of this study is to optimize and validate a classification algorithm that discriminates between sedentary, standing, and dynamic activities, and records postural transitions in hospitalized patients under free-living conditions. Optimization and validation in comparison to video analysis were performed in orthopedic and acutely hospitalized elderly patients with an accelerometer worn on the upper leg. Data segmentation window size (WS), amount of PA threshold (PA Th) and sensor orientation threshold (SO Th) were optimized in 25 patients, validation was performed in another 25. Sensitivity, specificity, accuracy, and (absolute) percentage error were used to assess the algorithm’s performance. Optimization resulted in the best performance with parameter settings: WS 4 s, PA Th 4.3 counts per second, SO Th 0.8 g. Validation showed that all activities were classified within acceptable limits (>80% sensitivity, specificity and accuracy, ±10% error), except for the classification of standing activity. As patients need to increase their PA and interrupt sedentary behavior, the algorithm is suitable for classifying PA in hospitalized patients.
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Koenders N, Weenk M, van de Belt TH, van Goor H, Hoogeboom TJ, Bredie SJH. Exploring barriers to physical activity of patients at the internal medicine and surgical wards: a retrospective analysis of continuously collected data. Disabil Rehabil 2019; 43:1883-1889. [PMID: 31691603 DOI: 10.1080/09638288.2019.1685013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
PURPOSE To analyse physical activity of patients during their hospital stay and to explore the relationship between physical activity and barriers to physical activity. METHODS This was a secondary analysis of physical activity data for patients admitted to the internal medicine and surgical wards. Physical activity data, collected with a wireless patch sensor, was operationalized as time spent lying, sitting/standing, and walking. Barriers to physical activity included patients' pain levels, the use of urinary catheters, intravenous tubing, oxygen lines, drains, and level of dependence. Regression analysis explored the relationship between physical activity and barriers to physical activity. RESULTS Physical activity data were collected in 39 patients (aged 27-88, mean 54 years) during hospital stay. Patients were admitted for a median of 10 d (interquartile range [IQR]: 7-15 d). These patients were lying for a median of 12.1 h (7.6-17.7), sitting/standing 11.8 h (6.3-15.7), and walking 0.1 h (0-0.3) per day. Time lying during the day related to pain levels (β = 0.4 h per unit increase in pain, p < 0.01) and drain use (β = 3.1 h, p < 0.01). CONCLUSIONS Patients spent the most time during the hospital stay lying in bed. Improved pain management and decreased drain use may be worth exploring to increase inpatient physical activity.Implications for rehabilitationContinuous monitoring of physical activity in patients during hospital stay is an important tool for health care professionals to improve multidisciplinary care and rehabilitation.Health care professionals should be aware of the necessity of adequate pain management and critically review the use of drains in order to improve physical activity of patients during hospital stay.Patients need extra support of health care professionals to increase physical activity during consecutive days of their hospital stay.
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Affiliation(s)
- Niek Koenders
- Department of Rehabilitation - Physical Therapy, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mariska Weenk
- Department of Surgery, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Tom H van de Belt
- Radboud Reshape Innovation Centre, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Harry van Goor
- Department of Surgery, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Thomas J Hoogeboom
- IQ Healthcare, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sebastian J H Bredie
- Department of Internal Medicine, Radboud Institute for Health Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
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