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Gao Z, Liu W, McDonough DJ, Zeng N, Lee JE. The Dilemma of Analyzing Physical Activity and Sedentary Behavior with Wrist Accelerometer Data: Challenges and Opportunities. J Clin Med 2021; 10:5951. [PMID: 34945247 PMCID: PMC8706489 DOI: 10.3390/jcm10245951] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 12/14/2021] [Accepted: 12/16/2021] [Indexed: 12/20/2022] Open
Abstract
Physical behaviors (e.g., physical activity and sedentary behavior) have been the focus among many researchers in the biomedical and behavioral science fields. The recent shift from hip- to wrist-worn accelerometers in these fields has signaled the need to develop novel approaches to process raw acceleration data of physical activity and sedentary behavior. However, there is currently no consensus regarding the best practices for analyzing wrist-worn accelerometer data to accurately predict individuals' energy expenditure and the times spent in different intensities of free-living physical activity and sedentary behavior. To this end, accurately analyzing and interpreting wrist-worn accelerometer data has become a major challenge facing many clinicians and researchers. In response, this paper attempts to review different methodologies for analyzing wrist-worn accelerometer data and offer cutting edge, yet appropriate analysis plans for wrist-worn accelerometer data in the assessment of physical behavior. In this paper, we first discuss the fundamentals of wrist-worn accelerometer data, followed by various methods of processing these data (e.g., cut points, steps per minute, machine learning), and then we discuss the opportunities, challenges, and directions for future studies in this area of inquiry. This is the most comprehensive review paper to date regarding the analysis and interpretation of free-living physical activity data derived from wrist-worn accelerometers, aiming to help establish a blueprint for processing wrist-derived accelerometer data.
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Affiliation(s)
- Zan Gao
- School of Kinesiology, University of Minnesota—Twin Cities, 1900 University Ave. SE, Minneapolis, MN 55455, USA
| | - Wenxi Liu
- Department of Physical Education, Shanghai Jiao Tong University, Shanghai 200240, China;
| | - Daniel J. McDonough
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota—Twin Cities, 420 Delaware St. SE, Minneapolis, MN 55455, USA;
| | - Nan Zeng
- Prevention Research Center, Department of Pediatrics, University of New Mexico Health Sciences Center, Albuquerque, NM 87131, USA;
| | - Jung Eun Lee
- Department of Applied Human Sciences, University of Minnesota—Duluth, 1216 Ordean Court SpHC 109, Duluth, MN 55812, USA;
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Backes A, Gupta T, Schmitz S, Fagherazzi G, van Hees V, Malisoux L. Advanced analytical methods to assess physical activity behavior using accelerometer time series: A scoping review. Scand J Med Sci Sports 2021; 32:18-44. [PMID: 34695249 PMCID: PMC9298329 DOI: 10.1111/sms.14085] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 10/12/2021] [Accepted: 10/18/2021] [Indexed: 11/29/2022]
Abstract
Physical activity (PA) is a complex human behavior, which implies that multiple dimensions need to be taken into account in order to reveal a complete picture of the PA behavior profile of an individual. This scoping review aimed to map advanced analytical methods and their summary variables, hereinafter referred to as wearable‐specific indicators of PA behavior (WIPAB), used to assess PA behavior. The strengths and limitations of those indicators as well as potential associations with certain health‐related factors were also investigated. Three databases (MEDLINE, Embase, and Web of Science) were screened for articles published in English between January 2010 and April 2020. Articles, which assessed the PA behavior, gathered objective measures of PA using tri‐axial accelerometers, and investigated WIPAB, were selected. All studies reporting WIPAB in the context of PA monitoring were synthesized and presented in four summary tables: study characteristics, details of the WIPAB, strengths, and limitations, and measures of association between those indicators and health‐related factors. In total, 7247 records were identified, of which 24 articles were included after assessing titles, abstracts, and full texts. Thirteen WIPAB were identified, which can be classified into three different categories specifically focusing on (1) the activity intensity distribution, (2) activity accumulation, and (3) the temporal correlation and regularity of the acceleration signal. Only five of the thirteen WIPAB identified in this review have been used in the literature so far to investigate the relationship between PA behavior and health, while they may provide useful additional information to the conventional PA variables.
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Affiliation(s)
- Anne Backes
- Physical Activity, Sport and Health Research Group, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Tripti Gupta
- Physical Activity, Sport and Health Research Group, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Susanne Schmitz
- Competence Center for Methodology and Statistics, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Guy Fagherazzi
- Deep Digital Phenotyping Research Unit, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
| | - Vincent van Hees
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Accelting, Almere, The Netherlands
| | - Laurent Malisoux
- Physical Activity, Sport and Health Research Group, Department of Population Health, Luxembourg Institute of Health, Strassen, Luxembourg
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Miranda-Duro MDC, Nieto-Riveiro L, Concheiro-Moscoso P, Groba B, Pousada T, Canosa N, Pereira J. Analysis of Older Adults in Spanish Care Facilities, Risk of Falling and Daily Activity Using Xiaomi Mi Band 2. SENSORS (BASEL, SWITZERLAND) 2021; 21:3341. [PMID: 34064993 PMCID: PMC8150783 DOI: 10.3390/s21103341] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 05/07/2021] [Accepted: 05/07/2021] [Indexed: 12/26/2022]
Abstract
BACKGROUND Presently the use of technological devices such as wearable devices has emerged. Physical activity monitoring with wearable sensors is an easy and non-intrusive approach to encourage preventive care for older adults. It may be useful to follow a continuous assessment of the risk of falling. The objective is to explore the relationship between the daily activity measured by Xiaomi Mi Band 2 and the risk of falling of older adults residing in or attending care facilities. METHODS A cross-sectional study was conducted on three different institutions located in Galicia (autonomous community) (Spain). RESULTS A total of 31 older adults were included in the study, with a mean age of 84 ± 8.71 years old. The main findings obtained were that a greater number of steps and distance could be related to a lower probability of falling, of dependency in basic activities of daily living, or of mobility problems. CONCLUSIONS The importance of focusing on daily steps, intrinsically related to the objective assessment of daily physical activity, is that it is a modifiable factor that impacts different aspects of health and quality of life.
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Affiliation(s)
- María del Carmen Miranda-Duro
- CITIC (Centre for Information and Communications Technology Research), TALIONIS Group, Elviña Campus, University of A Coruna, 15071 A Coruña, Spain; (M.d.C.M.-D.); (P.C.-M.); (B.G.); (T.P.); (N.C.); (J.P.)
- Department of Physiotherapy, Medicine and Biomedical Sciences, Faculty of Health Sciences, Oza Campus, University of A Coruna, 15071 A Coruña, Spain
| | - Laura Nieto-Riveiro
- CITIC (Centre for Information and Communications Technology Research), TALIONIS Group, Elviña Campus, University of A Coruna, 15071 A Coruña, Spain; (M.d.C.M.-D.); (P.C.-M.); (B.G.); (T.P.); (N.C.); (J.P.)
- Department of Health Sciences, Faculty of Health Sciences, Oza Campus, University of A Coruna, 15071 A Coruña, Spain
| | - Patricia Concheiro-Moscoso
- CITIC (Centre for Information and Communications Technology Research), TALIONIS Group, Elviña Campus, University of A Coruna, 15071 A Coruña, Spain; (M.d.C.M.-D.); (P.C.-M.); (B.G.); (T.P.); (N.C.); (J.P.)
- Department of Physiotherapy, Medicine and Biomedical Sciences, Faculty of Health Sciences, Oza Campus, University of A Coruna, 15071 A Coruña, Spain
| | - Betania Groba
- CITIC (Centre for Information and Communications Technology Research), TALIONIS Group, Elviña Campus, University of A Coruna, 15071 A Coruña, Spain; (M.d.C.M.-D.); (P.C.-M.); (B.G.); (T.P.); (N.C.); (J.P.)
- Department of Health Sciences, Faculty of Health Sciences, Oza Campus, University of A Coruna, 15071 A Coruña, Spain
| | - Thais Pousada
- CITIC (Centre for Information and Communications Technology Research), TALIONIS Group, Elviña Campus, University of A Coruna, 15071 A Coruña, Spain; (M.d.C.M.-D.); (P.C.-M.); (B.G.); (T.P.); (N.C.); (J.P.)
- Department of Health Sciences, Faculty of Health Sciences, Oza Campus, University of A Coruna, 15071 A Coruña, Spain
| | - Nereida Canosa
- CITIC (Centre for Information and Communications Technology Research), TALIONIS Group, Elviña Campus, University of A Coruna, 15071 A Coruña, Spain; (M.d.C.M.-D.); (P.C.-M.); (B.G.); (T.P.); (N.C.); (J.P.)
- Department of Health Sciences, Faculty of Health Sciences, Oza Campus, University of A Coruna, 15071 A Coruña, Spain
| | - Javier Pereira
- CITIC (Centre for Information and Communications Technology Research), TALIONIS Group, Elviña Campus, University of A Coruna, 15071 A Coruña, Spain; (M.d.C.M.-D.); (P.C.-M.); (B.G.); (T.P.); (N.C.); (J.P.)
- Department of Physiotherapy, Medicine and Biomedical Sciences, Faculty of Health Sciences, Oza Campus, University of A Coruna, 15071 A Coruña, Spain
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