1
|
Hegi H, Heitz J, Kredel R. Sensor-based augmented visual feedback for coordination training in healthy adults: a scoping review. Front Sports Act Living 2023; 5:1145247. [PMID: 37502095 PMCID: PMC10370279 DOI: 10.3389/fspor.2023.1145247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2023] [Accepted: 06/13/2023] [Indexed: 07/29/2023] Open
Abstract
Introduction Recent advances in sensor technology demonstrate the potential to enhance training regimes with sensor-based augmented visual feedback training systems for complex movement tasks in sports. Sensorimotor learning requires feedback that guides the learning process towards an optimal solution for the task to be learned, while considering relevant aspects of the individual control system-a process that can be summarized as learning or improving coordination. Sensorimotor learning can be fostered significantly by coaches or therapists providing additional external feedback, which can be incorporated very effectively into the sensorimotor learning process when chosen carefully and administered well. Sensor technology can complement existing measures and therefore improve the feedback provided by the coach or therapist. Ultimately, this sensor technology constitutes a means for autonomous training by giving augmented feedback based on physiological, kinetic, or kinematic data, both in real-time and after training. This requires that the key aspects of feedback administration that prevent excessive guidance can also be successfully automated and incorporated into such electronic devices. Methods After setting the stage from a computational perspective on motor control and learning, we provided a scoping review of the findings on sensor-based augmented visual feedback in complex sensorimotor tasks occurring in sports-related settings. To increase homogeneity and comparability of the results, we excluded studies focusing on modalities other than visual feedback and employed strict inclusion criteria regarding movement task complexity and health status of participants. Results We reviewed 26 studies that investigated visual feedback in training regimes involving healthy adults aged 18-65. We extracted relevant data regarding the chosen feedback and intervention designs, measured outcomes, and summarized recommendations from the literature. Discussion Based on these findings and the theoretical background on motor learning, we compiled a set of considerations and recommendations for the development and evaluation of future sensor-based augmented feedback systems in the interim. However, high heterogeneity and high risk of bias prevent a meaningful statistical synthesis for an evidence-based feedback design guidance. Stronger study design and reporting guidelines are necessary for future research in the context of complex skill acquisition.
Collapse
|
2
|
Facciorusso S, Spina S, Reebye R, Turolla A, Calabrò RS, Fiore P, Santamato A. Sensor-Based Rehabilitation in Neurological Diseases: A Bibliometric Analysis of Research Trends. Brain Sci 2023; 13:brainsci13050724. [PMID: 37239196 DOI: 10.3390/brainsci13050724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 04/20/2023] [Accepted: 04/24/2023] [Indexed: 05/28/2023] Open
Abstract
BACKGROUND As the field of sensor-based rehabilitation continues to expand, it is important to gain a comprehensive understanding of its current research landscape. This study aimed to conduct a bibliometric analysis to identify the most influential authors, institutions, journals, and research areas in this field. METHODS A search of the Web of Science Core Collection was performed using keywords related to sensor-based rehabilitation in neurological diseases. The search results were analyzed with CiteSpace software using bibliometric techniques, including co-authorship analysis, citation analysis, and keyword co-occurrence analysis. RESULTS Between 2002 and 2022, 1103 papers were published on the topic, with slow growth from 2002 to 2017, followed by a rapid increase from 2018 to 2022. The United States was the most active country, while the Swiss Federal Institute of Technology had the highest number of publications among institutions. Sensors published the most papers. The top keywords included rehabilitation, stroke, and recovery. The clusters of keywords comprised machine learning, specific neurological conditions, and sensor-based rehabilitation technologies. CONCLUSIONS This study provides a comprehensive overview of the current state of sensor-based rehabilitation research in neurological diseases, highlighting the most influential authors, journals, and research themes. The findings can help researchers and practitioners to identify emerging trends and opportunities for collaboration and can inform the development of future research directions in this field.
Collapse
Affiliation(s)
- Salvatore Facciorusso
- Department of Medical and Surgical Specialties and Dentistry, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy
- Spasticity and Movement Disorders "ReSTaRt", Unit Physical Medicine and Rehabilitation Section, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy
| | - Stefania Spina
- Spasticity and Movement Disorders "ReSTaRt", Unit Physical Medicine and Rehabilitation Section, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy
| | - Rajiv Reebye
- Division of Physical Medicine and Rehabilitation, Faculty of Medicine, University of British Columbia, Vancouver, BC V5Z 2G9, Canada
| | - Andrea Turolla
- Department of Biomedical and Neuromotor Sciences-DIBINEM, Alma Mater Studiorum Università di Bologna, 40138 Bologna, Italy
| | | | - Pietro Fiore
- Neurorehabilitation Unit, Institute of Bari, Istituti Clinici Scientifici Maugeri IRCCS, 70124 Bari, Italy
| | - Andrea Santamato
- Spasticity and Movement Disorders "ReSTaRt", Unit Physical Medicine and Rehabilitation Section, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy
| |
Collapse
|
3
|
Crowley P, Ikeda E, Islam SMS, Kildedal R, Schade Jacobsen S, Roslyng Larsen J, Johansson PJ, Hettiarachchi P, Aadahl M, Mork PJ, Straker L, Stamatakis E, Holtermann A, Gupta N. The Surveillance of Physical Activity, Sedentary Behavior, and Sleep: Protocol for the Development and Feasibility Evaluation of a Novel Measurement System. JMIR Res Protoc 2022; 11:e35697. [PMID: 35666571 PMCID: PMC9210205 DOI: 10.2196/35697] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 04/28/2022] [Accepted: 05/05/2022] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND There is increasing recognition of the need for more comprehensive surveillance data, including information on physical activity of all intensities, sedentary behavior, and sleep. However, meeting this need poses significant challenges for current surveillance systems, which are mainly reliant on self-report. OBJECTIVE The primary objective of this project is to develop and evaluate the feasibility of a sensor-based system for use in the surveillance of physical activity, sedentary behavior, and sleep (SurPASS) at a national level in Denmark. METHODS The SurPASS project involves an international, multidisciplinary team of researchers collaborating with an industrial partner. The SurPASS system consists of (1) a thigh-worn accelerometer with Bluetooth connectivity, (2) a smartphone app, (3) an integrated back end, facilitating the automated upload, analysis, storage, and provision of individualized feedback in a manner compliant with European Union regulations on data privacy, and (4) an administrator web interface (web application) to monitor progress. The system development and evaluation will be performed in 3 phases. These phases will include gathering user input and specifications (phase 1), the iterative development, evaluation, and refinement of the system (phase 2), and the feasibility evaluation (phase 3). RESULTS The project started in September 2020 and completed phase 2 in February 2022. Phase 3 began in March 2022 and results will be made available in 2023. CONCLUSIONS If feasible, the SurPASS system could be a catalyst toward large-scale, sensor-based surveillance of physical activity, sedentary behavior, and sleep. It could also be adapted for cohort and interventional research, thus contributing to the generation of evidence for both interventions and public health policies and recommendations. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID) DERR1-10.2196/35697.
Collapse
Affiliation(s)
- Patrick Crowley
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| | - Erika Ikeda
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | | | - Rasmus Kildedal
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| | | | - Jon Roslyng Larsen
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| | - Peter J Johansson
- Occupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Pasan Hettiarachchi
- Occupational and Environmental Medicine, Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Mette Aadahl
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Research and Prevention, Bispebjerg and Fredriksberg Hospital, Copenhagen, Denmark
| | - Paul Jarle Mork
- Department of Public Health and Nursing, Faculty of Medicine, Norwegian University of Science and Technology, Trondheim, Norway
| | - Leon Straker
- School of Allied Health and enAble Institute, Curtin University, Perth, Australia
| | - Emmanuel Stamatakis
- Charles Perkins Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
| | - Andreas Holtermann
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| | - Nidhi Gupta
- The National Research Centre for the Working Environment, Copenhagen, Denmark
| |
Collapse
|
4
|
Mohammed M, Riad K, Alqahtani N. Efficient IoT-Based Control for a Smart Subsurface Irrigation System to Enhance Irrigation Management of Date Palm. Sensors (Basel) 2021; 21:3942. [PMID: 34201041 DOI: 10.3390/s21123942] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 06/02/2021] [Accepted: 06/04/2021] [Indexed: 12/02/2022]
Abstract
Drought is the most severe problem for agricultural production, and the intensity of this problem is increasing in most cultivated areas around the world. Hence improving water productivity is the primary purpose of sustainable agriculture. This study aimed to use cloud IoT solutions to control a modern subsurface irrigation system for improving irrigation management of date palms in arid regions. To achieve this goal, we designed, constructed, and validated the performance of a fully automated controlled subsurface irrigation system (CSIS) to monitor and control the irrigation water amount remotely. The CSIS is based on an autonomous sensors network to instantly collect the climatic parameters and volumetric soil water content in the study area. Therefore, we employed the ThingSpeak cloud platform to host sensor readings, perform algorithmic analysis, instant visualize the live data, create event-based alerts to the user, and send instructions to the IoT devices. The validation of the CSIS proved that automatically irrigating date palm trees controlled by the sensor-based irrigation scheduling (S-BIS) is more efficient than the time-based irrigation scheduling (T-BIS). The S-BIS provided the date palm with the optimum irrigation water amount at the opportune time directly in the functional root zone. Generally, the S-BIS and T-BIS of CSIS reduced the applied irrigation water amount by 64.1% and 61.2%, respectively, compared with traditional surface irrigation (TSI). The total annual amount of applied irrigation water for CSIS with S-BIS method, CSIS with T-BIS method, and TSI was 21.04, 22.76, and 58.71 m3 palm−1, respectively. The water productivity at the CSIS with S-BIS (1.783 kg m−3) and T-BIS (1.44 kg m−3) methods was significantly higher compared to the TSI (0.531 kg m−3). The CSIS with the S-BIS method kept the volumetric water content in the functional root zone next to the field capacity compared to the T-BIS method. The deigned CSIS with the S-BIS method characterized by the positive impact on the irrigation water management and enhancement on fruit yield of the date palm is quite proper for date palm irrigation in the arid regions.
Collapse
|
5
|
Abel B, Bongartz M, Eckert T, Ullrich P, Beurskens R, Mellone S, Bauer JM, Lamb SE, Hauer K. Will We Do If We Can? Habitual Qualitative and Quantitative Physical Activity in Multi-Morbid, Older Persons with Cognitive Impairment. Sensors (Basel) 2020; 20:s20247208. [PMID: 33339293 PMCID: PMC7766414 DOI: 10.3390/s20247208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Revised: 12/04/2020] [Accepted: 12/14/2020] [Indexed: 11/16/2022]
Abstract
This study aimed to identify determinants of quantitative dimensions of physical activity (PA; duration, frequency, and intensity) in community-dwelling, multi-morbid, older persons with cognitive impairment (CI). In addition, qualitative and quantitative aspects of habitual PA have been described. Quantitative PA and qualitative gait characteristics while walking straight and while walking turns were documented by a validated, sensor-based activity monitor. Univariate and multiple linear regression analyses were performed to delineate associations of quantitative PA dimensions with qualitative characteristics of gait performance and further potential influencing factors (motor capacity measures, demographic, and health-related parameters). In 94 multi-morbid, older adults (82.3 ± 5.9 years) with CI (Mini-Mental State Examination score: 23.3 ± 2.4), analyses of quantitative and qualitative PA documented highly inactive behavior (89.6% inactivity) and a high incidence of gait deficits, respectively. The multiple regression models (adjusted R2 = 0.395–0.679, all p < 0.001) identified specific qualitative gait characteristics as independent determinants for all quantitative PA dimensions, whereas motor capacity was an independent determinant only for the PA dimension duration. Demographic and health-related parameters were not identified as independent determinants. High associations between innovative, qualitative, and established, quantitative PA performances may suggest gait quality as a potential target to increase quantity of PA in multi-morbid, older persons.
Collapse
Affiliation(s)
- Bastian Abel
- Department of Geriatric Research, AGAPLESION Bethanien Hospital Heidelberg, Geriatric Center at the University of Heidelberg, 69126 Heidelberg, Germany; (B.A.); (M.B.); (T.E.); (P.U.); (R.B.); (J.M.B.)
- Center for Geriatric Medicine, Heidelberg University, 69126 Heidelberg, Germany
| | - Martin Bongartz
- Department of Geriatric Research, AGAPLESION Bethanien Hospital Heidelberg, Geriatric Center at the University of Heidelberg, 69126 Heidelberg, Germany; (B.A.); (M.B.); (T.E.); (P.U.); (R.B.); (J.M.B.)
- Network Aging Research (NAR), Heidelberg University, 69115 Heidelberg, Germany
| | - Tobias Eckert
- Department of Geriatric Research, AGAPLESION Bethanien Hospital Heidelberg, Geriatric Center at the University of Heidelberg, 69126 Heidelberg, Germany; (B.A.); (M.B.); (T.E.); (P.U.); (R.B.); (J.M.B.)
- Department for Social and Health Sciences in Sport, Institute of Sports and Sports Science, Karlsruhe Institute of Technology, 76131 Karlsruhe, Germany
| | - Phoebe Ullrich
- Department of Geriatric Research, AGAPLESION Bethanien Hospital Heidelberg, Geriatric Center at the University of Heidelberg, 69126 Heidelberg, Germany; (B.A.); (M.B.); (T.E.); (P.U.); (R.B.); (J.M.B.)
| | - Rainer Beurskens
- Department of Geriatric Research, AGAPLESION Bethanien Hospital Heidelberg, Geriatric Center at the University of Heidelberg, 69126 Heidelberg, Germany; (B.A.); (M.B.); (T.E.); (P.U.); (R.B.); (J.M.B.)
- Department of Health and Social Affairs, FHM Bielefeld, University of Applied Sciences, 33602 Bielefeld, Germany
| | - Sabato Mellone
- Department of Electrical, Electronic, and Information Engineering, University of Bologna, 40136 Bologna, Italy;
| | - Jürgen M. Bauer
- Department of Geriatric Research, AGAPLESION Bethanien Hospital Heidelberg, Geriatric Center at the University of Heidelberg, 69126 Heidelberg, Germany; (B.A.); (M.B.); (T.E.); (P.U.); (R.B.); (J.M.B.)
- Center for Geriatric Medicine, Heidelberg University, 69126 Heidelberg, Germany
| | - Sallie E. Lamb
- Institute of Health Research, University of Exeter, South Cloisters, St. Luke’s Campus, Exeter EX1 2LU, UK;
| | - Klaus Hauer
- Department of Geriatric Research, AGAPLESION Bethanien Hospital Heidelberg, Geriatric Center at the University of Heidelberg, 69126 Heidelberg, Germany; (B.A.); (M.B.); (T.E.); (P.U.); (R.B.); (J.M.B.)
- Correspondence: ; Tel.: +49-6221-319-1532
| |
Collapse
|
6
|
Zhang N, Su B, Chan PT, Miao T, Wang P, Li Y. Infection Spread and High-Resolution Detection of Close Contact Behaviors. Int J Environ Res Public Health 2020; 17:E1445. [PMID: 32102305 PMCID: PMC7068293 DOI: 10.3390/ijerph17041445] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 02/15/2020] [Accepted: 02/20/2020] [Indexed: 12/22/2022]
Abstract
Knowledge of human behaviors is important for improving indoor-environment design, building-energy efficiency, and productivity, and for studies of infection spread. However, such data are lacking. In this study, we designed a device for detecting and recording, second by second, the 3D indoor positioning and head and body motions of each graduate student in an office. From more than 400 person hours of data. Students spent 92.2%, 4.1%, 2.9%, and 0.8% of their time in their own office cubicles, other office cubicles, aisles, and areas near public facilities, respectively. They spent 9.7% of time in close contact, and each student averagely had 4.0 close contacts/h. Students spent long time on close contact in the office which may lead to high infection risk. The average interpersonal distance during close contact was 0.81 m. When sitting, students preferred small relative face orientation angle. Pairs of standing students preferred a face-to-face orientation during close contact which means this pattern had a lower infection risk via close contact. Probability of close contact decreased exponentially with the increasing distance between two students' cubicles. Data on human behaviour during close contact is helpful for infection risk analysis and infection control and prevention.
Collapse
Affiliation(s)
- Nan Zhang
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong 999077, China; (N.Z.); (P.-T.C.); (T.M.); (P.W.)
| | - Boni Su
- China Electric Power Planning & Engineering Institute, Beijing 100120, China;
| | - Pak-To Chan
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong 999077, China; (N.Z.); (P.-T.C.); (T.M.); (P.W.)
| | - Te Miao
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong 999077, China; (N.Z.); (P.-T.C.); (T.M.); (P.W.)
| | - Peihua Wang
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong 999077, China; (N.Z.); (P.-T.C.); (T.M.); (P.W.)
| | - Yuguo Li
- Department of Mechanical Engineering, The University of Hong Kong, Pokfulam Road, Hong Kong 999077, China; (N.Z.); (P.-T.C.); (T.M.); (P.W.)
| |
Collapse
|
7
|
Fillekes MP, Kim EK, Trumpf R, Zijlstra W, Giannouli E, Weibel R. Assessing Older Adults' Daily Mobility: A Comparison of GPS-Derived and Self-Reported Mobility Indicators. Sensors (Basel) 2019; 19:s19204551. [PMID: 31635100 PMCID: PMC6833043 DOI: 10.3390/s19204551] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Revised: 10/12/2019] [Accepted: 10/15/2019] [Indexed: 12/24/2022]
Abstract
Interest in global positioning system (GPS)-based mobility assessment for health and aging research is growing, and with it the demand for validated GPS-based mobility indicators. Time out of home (TOH) and number of activity locations (#ALs) are two indicators that are often derived from GPS data, despite lacking consensus regarding thresholds to be used to extract those as well as limited knowledge about their validity. Using 7 days of GPS and diary data of 35 older adults, we make the following three main contributions. First, we perform a sensitivity analysis to investigate how using spatial and temporal thresholds to compute TOH and #ALs affects the agreement between self-reported and GPS-based indicators. Second, we show how daily self-reported and GPS-derived mobility indicators are compared. Third, we explore whether the type and duration of self-reported activity events are related to the degree of correspondence between reported and GPS event. Highest indicator agreement was found for temporal interpolation (Tmax) of up to 5 h for both indicators, a radius (Dmax) to delineate home between 100 and 200 m for TOH, and for #ALs a spatial extent (Dmax) between 125 and 200 m, and temporal extent (Tmin) between 5 and 6 min to define an activity location. High agreement between self-reported and GPS-based indicators is obtained for TOH and moderate agreement for #ALs. While reported event type and duration impact on whether a reported event has a matching GPS event, indoor and outdoor events are detected at equal proportions. This work will help future studies to choose optimal threshold settings and will provide knowledge about the validity of mobility indicators.
Collapse
Affiliation(s)
- Michelle Pasquale Fillekes
- Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland.
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Andreasstrasse 15, 8050 Zurich, Switzerland.
| | - Eun-Kyeong Kim
- Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland.
- University Research Priority Program "Dynamics of Healthy Aging", University of Zurich, Andreasstrasse 15, 8050 Zurich, Switzerland.
| | - Rieke Trumpf
- Institute of Movement and Sport Gerontology, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany.
- Department of Geriatric Psychiatry and Psychotherapy, LVR Hospital Cologne, Wilhelm-Griesinger-Straße 23, 51109 Cologne, Germany.
| | - Wiebren Zijlstra
- Institute of Movement and Sport Gerontology, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany.
| | - Eleftheria Giannouli
- Institute of Movement and Sport Gerontology, German Sport University Cologne, Am Sportpark Müngersdorf 6, 50933 Cologne, Germany.
| | - Robert Weibel
- Department of Geography, University of Zurich, Winterthurerstrasse 190, 8057 Zurich, Switzerland.
| |
Collapse
|