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Boboc RG, Butilă EV, Butnariu S. Leveraging Wearable Sensors in Virtual Reality Driving Simulators: A Review of Techniques and Applications. SENSORS (BASEL, SWITZERLAND) 2024; 24:4417. [PMID: 39001197 PMCID: PMC11244598 DOI: 10.3390/s24134417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/11/2024] [Revised: 07/02/2024] [Accepted: 07/05/2024] [Indexed: 07/16/2024]
Abstract
Virtual reality (VR) driving simulators are very promising tools for driver assessment since they provide a controlled and adaptable setting for behavior analysis. At the same time, wearable sensor technology provides a well-suited and valuable approach to evaluating the behavior of drivers and their physiological or psychological state. This review paper investigates the potential of wearable sensors in VR driving simulators. Methods: A literature search was performed on four databases (Scopus, Web of Science, Science Direct, and IEEE Xplore) using appropriate search terms to retrieve scientific articles from a period of eleven years, from 2013 to 2023. Results: After removing duplicates and irrelevant papers, 44 studies were selected for analysis. Some important aspects were extracted and presented: the number of publications per year, countries of publication, the source of publications, study aims, characteristics of the participants, and types of wearable sensors. Moreover, an analysis and discussion of different aspects are provided. To improve car simulators that use virtual reality technologies and boost the effectiveness of particular driver training programs, data from the studies included in this systematic review and those scheduled for the upcoming years may be of interest.
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Affiliation(s)
- Răzvan Gabriel Boboc
- Department of Automotive and Transport Engineering, Transilvania University of Brasov, RO-500036 Brasov, Romania
| | - Eugen Valentin Butilă
- Department of Automotive and Transport Engineering, Transilvania University of Brasov, RO-500036 Brasov, Romania
| | - Silviu Butnariu
- Department of Automotive and Transport Engineering, Transilvania University of Brasov, RO-500036 Brasov, Romania
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Silva-Batista C, de Almeida FO, Wilhelm JL, Horak FB, Mancini M, King LA. Telerehabilitation by Videoconferencing for Balance and Gait in People with Parkinson's Disease: A Scoping Review. Geriatrics (Basel) 2024; 9:66. [PMID: 38920422 PMCID: PMC11202546 DOI: 10.3390/geriatrics9030066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2024] [Revised: 05/14/2024] [Accepted: 05/21/2024] [Indexed: 06/27/2024] Open
Abstract
Although supervised and real-time telerehabilitation by videoconferencing is now becoming common for people with Parkinson's disease (PD), its efficacy for balance and gait is still unclear. This paper uses a scoping approach to review the current evidence on the effects of telerehabilitation by videoconferencing on balance and gait for patients with PD. We also explored whether studies have used wearable technology during telerehabilitation to assess and treat balance and gait via videoconferencing. Literature searches were conducted using PubMed, ISI's Web of Knowledge, Cochrane's Library, and Embase. The data were extracted for study design, treatment, and outcomes. Fourteen studies were included in this review. Of these, seven studies investigated the effects of telerehabilitation (e.g., tele-yoga and adapted physiotherapy exercises) on balance and gait measures (e.g., self-reported balance, balance scale, walking speed, mobility, and motor symptoms) using videoconferencing in both assessment and treatment. The telerehabilitation programs by videoconferencing were feasible and safe for people with PD; however, the efficacy still needs to be determined, as only four studies had a parallel group. In addition, no study used wearable technology. Robust evidence of the effects of telerehabilitation by videoconferencing on balance and gait for patients with PD was not found, suggesting that future powered, prospective, and robust clinical trials are needed.
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Affiliation(s)
- Carla Silva-Batista
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA; (C.S.-B.); (J.L.W.); (F.B.H.); (M.M.)
- Exercise Neuroscience Research Group, University of São Paulo, São Paulo 05508-070, Brazil;
| | | | - Jennifer L. Wilhelm
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA; (C.S.-B.); (J.L.W.); (F.B.H.); (M.M.)
| | - Fay B. Horak
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA; (C.S.-B.); (J.L.W.); (F.B.H.); (M.M.)
| | - Martina Mancini
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA; (C.S.-B.); (J.L.W.); (F.B.H.); (M.M.)
| | - Laurie A. King
- Department of Neurology, Oregon Health and Science University, Portland, OR 97239, USA; (C.S.-B.); (J.L.W.); (F.B.H.); (M.M.)
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Evans S. Sacroiliac Joint Dysfunction in Endurance Runners Using Wearable Technology as a Clinical Monitoring Tool: Systematic Review. JMIR BIOMEDICAL ENGINEERING 2024; 9:e46067. [PMID: 38875697 PMCID: PMC11148519 DOI: 10.2196/46067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2023] [Revised: 10/02/2023] [Accepted: 10/30/2023] [Indexed: 06/16/2024] Open
Abstract
BACKGROUND In recent years, researchers have delved into the relationship between the anatomy and biomechanics of sacroiliac joint (SIJ) pain and dysfunction in endurance runners to elucidate the connection between lower back pain and the SIJ. However, the majority of SIJ pain and dysfunction cases are diagnosed and managed through a traditional athlete-clinician arrangement, where the athlete must attend regular in-person clinical appointments with various allied health professionals. Wearable sensors (wearables) are increasingly serving as a clinical diagnostic tool to monitor an athlete's day-to-day activities remotely, thus eliminating the necessity for in-person appointments. Nevertheless, the extent to which wearables are used in a remote setting to manage SIJ dysfunction in endurance runners remains uncertain. OBJECTIVE This study aims to conduct a systematic review of the literature to enhance our understanding regarding the use of wearables in both in-person and remote settings for biomechanical-based rehabilitation in SIJ dysfunction among endurance runners. In addressing this issue, the overarching goal was to explore how wearables can contribute to the clinical diagnosis (before, during, and after) of SIJ dysfunction. METHODS Three online databases, including PubMed, Scopus, and Google Scholar, were searched using various combinations of keywords. Initially, a total of 4097 articles were identified. After removing duplicates and screening articles based on inclusion and exclusion criteria, 45 articles were analyzed. Subsequently, 21 articles were included in this study. The quality of the investigation was assessed using the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) evidence-based minimum set of items for reporting in systematic reviews. RESULTS Among the 21 studies included in this review, more than half of the investigations were literature reviews focusing on wearable sensors in the diagnosis and treatment of SIJ pain, wearable movement sensors for rehabilitation, or a combination of both for SIJ gait analysis in an intelligent health care setting. As many as 4 (19%) studies were case reports, and only 1 study could be classified as fully experimental. One paper was classified as being at the "pre" stage of SIJ dysfunction, while 6 (29%) were identified as being at the "at" stage of classification. Significantly fewer studies attempted to capture or classify actual SIJ injuries, and no study directly addressed the injury recovery stage. CONCLUSIONS SIJ dysfunction remains underdiagnosed and undertreated in endurance runners. Moreover, there is a lack of clear diagnostic or treatment pathways using wearables remotely, despite the availability of validated technology. Further research of higher quality is recommended to investigate SIJ dysfunction in endurance runners and explore the use of wearables for rehabilitation in remote settings.
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Affiliation(s)
- Stuart Evans
- School of Education, La Trobe University, Melbourne, Australia
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Gebreheat G, Goman A, Porter-Armstrong A. The use of home-based digital technology to support post-stroke upper limb rehabilitation: A scoping review. Clin Rehabil 2024; 38:60-71. [PMID: 37469176 PMCID: PMC10631286 DOI: 10.1177/02692155231189257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 07/05/2023] [Indexed: 07/21/2023]
Abstract
OBJECTIVE To identify, map and synthesize the extent and nature of existing studies on the use of home-based digital technology to support post-stroke upper limb rehabilitation. DATA SOURCES A comprehensive literature search was completed between 30 May 2022 and 05 April 2023, from seven online databases (CINAHL, Cochrane Library, PubMed, ScienceDirect, IEEExplore, Web of Science and PEDro), Google Scholar and the reference lists of already identified articles. METHODS A scoping review was conducted according to Arksey and O'Malley (2005), and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews. All English-language studies reporting on the use of home-based digital technology to support upper limb post-stroke rehabilitation were eligible for inclusion. RESULTS The search generated a total of 1895 records, of which 76 articles met the inclusion criteria. Of these, 52 were experimental studies and the rest, qualitative, case series and case studies. Of the overall 2149 participants, 2028 were stroke survivors with upper limb impairment. The majority of studies were aimed at developing, designing and/or assessing the feasibility, acceptability and efficacy of a digital system for poststroke upper limb rehabilitation in home settings. The thematic analysis found six major categories: Tele-rehabilitation (n = 29), games (n = 45), virtual reality (n = 26), sensor (n = 22), mobile technology (n = 22), and robotics (n = 8). CONCLUSION The digital technologies used in post-stroke upper limb rehabilitation were multimodal, and system-based comprising telerehabilitation, gamification, virtual reality, mobile technology, sensors and robotics. Furthermore, future research should focus to determine the effectiveness of these modalities.
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Affiliation(s)
- Gdiom Gebreheat
- School of Health and Social Care, Edinburgh Napier University, Edinburgh, UK
| | - Adele Goman
- School of Health and Social Care, Edinburgh Napier University, Edinburgh, UK
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Muñoz-Urtubia N, Vega-Muñoz A, Estrada-Muñoz C, Salazar-Sepúlveda G, Contreras-Barraza N, Salinas-Martínez N, Méndez-Celis P, Carmelo-Adsuar J. Wearable biosensors for human health: A bibliometric analysis from 2007 to 2022. Digit Health 2024; 10:20552076241256876. [PMID: 38882252 PMCID: PMC11179482 DOI: 10.1177/20552076241256876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/18/2024] Open
Abstract
Objective This study aimed to determine the status of scientific production on biosensor usage for human health monitoring. Methods We used bibliometrics based on the data and metadata retrieved from the Web of Science between 2007 and 2022. Articles unrelated to health and medicine were excluded. The databases were processed using the VOSviewer software and auxiliary spreadsheets. Data extraction yielded 275 articles published in 161 journals, mainly concentrated on 13 journals and 881 keywords plus. Results The keywords plus of high occurrences were estimated at 27, with seven to 30 occurrences. From the 1595 identified authors, 125 were consistently connected in the coauthorship network in the total set and were grouped into nine clusters. Using Lotka's law, we identified 24 prolific authors, and Hirsch index analysis revealed that 45 articles were cited more than 45 times. Crosses were identified between 17 articles in the Hirsch index and 17 prolific authors, highlighting the presence of a large set of prolific authors from various interconnected clusters, a triad, and a solitary prolific author. Conclusion An exponential trend was observed in biosensor research for health monitoring, identifying areas of innovation, collaboration, and technological challenges that can guide future research on this topic.
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Affiliation(s)
- Nicolás Muñoz-Urtubia
- International Graduate School, University of Extremadura, Caceres, Spain
- Instituto de Ciencias de la Educación, Universidad Austral de Chile, Valdivia, Chile
| | - Alejandro Vega-Muñoz
- Facultad de Medicina y Ciencias de la Salud, Universidad Central de Chile, Santiago, Chile
- Facultad de Ciencias Empresariales, Universidad Arturo Prat, Iquique, Chile
| | - Carla Estrada-Muñoz
- Facultad de Ciencias Biológicas, Universidad de Concepción, Concepción, Chile
| | - Guido Salazar-Sepúlveda
- Facultad de Ingeniería, Universidad Católica de la Santísima Concepción, Concepción, Chile
- Facultad de Ingeniería y Negocios, Universidad de Las Américas, Concepción, Chile
| | | | - Nicolás Salinas-Martínez
- Facultad de Ciencias Económicas, Administrativas y Contables, Universidad Nacional Autónoma de Honduras, Tegucigalpa, Honduras
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Neumann-Langen MV, Ochs BG, Lützner J, Postler A, Kirschberg J, Sehat K, Selig M, Grupp TM. Musculoskeletal Rehabilitation: New Perspectives in Postoperative Care Following Total Knee Arthroplasty Using an External Motion Sensor and a Smartphone Application for Remote Monitoring. J Clin Med 2023; 12:7163. [PMID: 38002775 PMCID: PMC10672501 DOI: 10.3390/jcm12227163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Revised: 11/11/2023] [Accepted: 11/17/2023] [Indexed: 11/26/2023] Open
Abstract
BACKGROUND The number of total knee replacements performed annually is steadily increasing. Parallel options for postoperative care are decreasing, which reduces patient satisfaction. External devices to support physical rehabilitation and health monitoring will improve patient satisfaction and postoperative care. METHODS In a prospective, international multicenter study, patients were asked to use an external motion sensor and a smartphone application during the postoperative course of primary total knee arthroplasty. The collected data were transferred to a data platform, allowing for the real-time evaluation of patient data. RESULTS In three participating centers, 98 patients were included. The general acceptance of using the sensor and app was high, with an overall compliance in study participation rate of up to 76%. The early results showed a significant improvement in the overall quality of life (p < 0.001) and significant reductions in pain (p < 0.01) and depression (p < 0.001). CONCLUSIONS The early results of this clinical and multicenter study emphasize that there is a high interest in and acceptance of digital solutions in patients' treatment pathways. Motion sensor and smartphone applications support patients in early rehabilitation.
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Affiliation(s)
| | - Björn Gunnar Ochs
- Klinikum Konstanz, Department of Orthopaedic and Trauma Surgery, Mainaustrasse 35, 78464 Konstanz, Germany;
| | - Jörg Lützner
- University Center of Orthopaedic, Trauma and Plastic Surgery, University Hospital Carl Gustav Carus Dresden, TU Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; (J.L.); (A.P.)
| | - Anne Postler
- University Center of Orthopaedic, Trauma and Plastic Surgery, University Hospital Carl Gustav Carus Dresden, TU Dresden, Fetscherstrasse 74, 01307 Dresden, Germany; (J.L.); (A.P.)
| | - Julia Kirschberg
- Waldkliniken Eisenberg GmbH, Klosterlausnitzer Strasse 81, 07607 Eisenberg, Germany;
| | - Khosrow Sehat
- Department of Trauma and Orthopaedics, Nottingham University Hospitals NHS Trust, Nottingham NG7 2UH, UK;
| | - Marius Selig
- Aesculap AG Research and Development and Medical Scientific Affairs, Am Aesculap-Platz, 78532 Tuttlingen, Germany; (M.S.); (T.M.G.)
| | - Thomas M. Grupp
- Aesculap AG Research and Development and Medical Scientific Affairs, Am Aesculap-Platz, 78532 Tuttlingen, Germany; (M.S.); (T.M.G.)
- Department of Orthopaedic and Trauma Surgery, Musculoskeletal University Center Munich (MUM), LMULudwigs Maximilian University, 81377 Munich, Germany
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Liu T, Liu X. Perspectives in Wearable Systems in the Human-Robot Interaction (HRI) Field. SENSORS (BASEL, SWITZERLAND) 2023; 23:8315. [PMID: 37837147 PMCID: PMC10575189 DOI: 10.3390/s23198315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/29/2023] [Accepted: 10/07/2023] [Indexed: 10/15/2023]
Abstract
Due to the advantages of ease of use, less motion disturbance, and low cost, wearable systems have been widely used in the human-machine interaction (HRI) field. However, HRI in complex clinical rehabilitation scenarios has further requirements for wearable sensor systems, which has aroused the interest of many researchers. However, the traditional wearable system has problems such as low integration, limited types of measurement data, and low accuracy, causing a gap with the actual needs of HRI. This paper will introduce the latest progress in the current wearable systems of HRI from four aspects. First of all, it introduces the breakthroughs of current research in system integration, which includes processing chips and flexible sensing modules to reduce the system's volume and increase battery life. After that, this paper reviews the latest progress of wearable systems in electrochemical measurement, which can extract single or multiple biomarkers from biological fluids such as sweat. In addition, the clinical application of non-invasive wearable systems is introduced, which solves the pain and discomfort problems caused by traditional clinical invasive measurement equipment. Finally, progress in the combination of current wearable systems and the latest machine-learning methods is shown, where higher accuracy and indirect acquisition of data that cannot be directly measured is achieved. From the evidence presented, we believe that the development trend of wearable systems in HRI is heading towards high integration, multi-electrochemical measurement data, and clinical and intelligent development.
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Ju F, Wang Y, Yin B, Zhao M, Zhang Y, Gong Y, Jiao C. Microfluidic Wearable Devices for Sports Applications. MICROMACHINES 2023; 14:1792. [PMID: 37763955 PMCID: PMC10535163 DOI: 10.3390/mi14091792] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/26/2023] [Revised: 09/14/2023] [Accepted: 09/18/2023] [Indexed: 09/29/2023]
Abstract
This study aimed to systematically review the application and research progress of flexible microfluidic wearable devices in the field of sports. The research team thoroughly investigated the use of life signal-monitoring technology for flexible wearable devices in the domain of sports. In addition, the classification of applications, the current status, and the developmental trends of similar products and equipment were evaluated. Scholars expect the provision of valuable references and guidance for related research and the development of the sports industry. The use of microfluidic detection for collecting biomarkers can mitigate the impact of sweat on movements that are common in sports and can also address the issue of discomfort after prolonged use. Flexible wearable gadgets are normally utilized to monitor athletic performance, rehabilitation, and training. Nevertheless, the research and development of such devices is limited, mostly catering to professional athletes. Devices for those who are inexperienced in sports and disabled populations are lacking. Conclusions: Upgrading microfluidic chip technology can lead to accurate and safe sports monitoring. Moreover, the development of multi-functional and multi-site devices can provide technical support to athletes during their training and competitions while also fostering technological innovation in the field of sports science.
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Affiliation(s)
- Fangyuan Ju
- College of Physical Education, Yangzhou University, Yangzhou 225127, China; (F.J.); (Y.W.); (M.Z.); (Y.Z.)
| | - Yujie Wang
- College of Physical Education, Yangzhou University, Yangzhou 225127, China; (F.J.); (Y.W.); (M.Z.); (Y.Z.)
| | - Binfeng Yin
- School of Mechanical Engineering, Yangzhou University, Yangzhou 225127, China;
| | - Mengyun Zhao
- College of Physical Education, Yangzhou University, Yangzhou 225127, China; (F.J.); (Y.W.); (M.Z.); (Y.Z.)
| | - Yupeng Zhang
- College of Physical Education, Yangzhou University, Yangzhou 225127, China; (F.J.); (Y.W.); (M.Z.); (Y.Z.)
| | - Yuanyuan Gong
- Institute of Physical Education, Shanghai Normal University, Shanghai 200234, China;
| | - Changgeng Jiao
- Institute of Physical Education, Shanghai Normal University, Shanghai 200234, China;
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Zha Q, Xu Z, Cai X, Zhang G, Shen X. Wearable rehabilitation wristband for distal radius fractures. Front Neurosci 2023; 17:1238176. [PMID: 37781255 PMCID: PMC10536142 DOI: 10.3389/fnins.2023.1238176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Accepted: 08/07/2023] [Indexed: 10/03/2023] Open
Abstract
Background Distal radius fractures are a common type of fracture. For patients treated with closed reduction with splinting, a period of rehabilitation is still required after the removal of the splint. However, there is a general lack of attention and low compliance to rehabilitation training during this period, so it is necessary to build a rehabilitation training monitoring system to improve the efficiency of patients' rehabilitation. Methods A wearable rehabilitation training wristband was proposed, which could be used in the patient's daily rehabilitation training scenario and could recognize four common wrist rehabilitation actions in real-time by using three thin film pressure sensors to detect the pressure change curve at three points on the wrist. An algorithmic framework for classifying rehabilitation training actions was proposed. In our framework, an action pre-detection strategy was designed to exclude false detections caused by switching initial gestures during rehabilitation training and wait for the arrival of the complete signal. To classify the action signals into four categories, firstly an autoencoder was used to downscale the original signal. Six SVMs were then used for evaluation and voting, and the final action with the highest number of votes would be used as the prediction result. Results Experimental results showed that the proposed algorithmic framework achieved an average recognition accuracy of 89.62%, an average recognition recall of 88.93%, and an f1 score of 89.27% on the four rehabilitation training actions. Conclusion The developed device has the advantages of being small size and easy to wear, which can quickly and accurately identify and classify four common rehabilitation training actions. It can easily be combined with peripheral devices and technologies (e.g., cell phones, computers, Internet) to build different rehabilitation training scenarios, making it worthwhile to use and promote in clinical settings.
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Affiliation(s)
- Qing Zha
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, China
| | - Zeou Xu
- School of Biomedical Engineering (Suzhou), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Science, Suzhou, China
| | - Xuefeng Cai
- Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou, China
| | - Guodong Zhang
- Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou, China
| | - Xiaofeng Shen
- Suzhou TCM Hospital Affiliated to Nanjing University of Chinese Medicine, Suzhou, China
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Osama M, Ateya AA, Sayed MS, Hammad M, Pławiak P, Abd El-Latif AA, Elsayed RA. Internet of Medical Things and Healthcare 4.0: Trends, Requirements, Challenges, and Research Directions. SENSORS (BASEL, SWITZERLAND) 2023; 23:7435. [PMID: 37687891 PMCID: PMC10490658 DOI: 10.3390/s23177435] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 08/15/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023]
Abstract
Healthcare 4.0 is a recent e-health paradigm associated with the concept of Industry 4.0. It provides approaches to achieving precision medicine that delivers healthcare services based on the patient's characteristics. Moreover, Healthcare 4.0 enables telemedicine, including telesurgery, early predictions, and diagnosis of diseases. This represents an important paradigm for modern societies, especially with the current situation of pandemics. The release of the fifth-generation cellular system (5G), the current advances in wearable device manufacturing, and the recent technologies, e.g., artificial intelligence (AI), edge computing, and the Internet of Things (IoT), are the main drivers of evolutions of Healthcare 4.0 systems. To this end, this work considers introducing recent advances, trends, and requirements of the Internet of Medical Things (IoMT) and Healthcare 4.0 systems. The ultimate requirements of such networks in the era of 5G and next-generation networks are discussed. Moreover, the design challenges and current research directions of these networks. The key enabling technologies of such systems, including AI and distributed edge computing, are discussed.
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Affiliation(s)
- Manar Osama
- Department of Electronics and Communications Engineering, Zagazig University, Zagazig 44519, Egypt; (M.O.); (M.S.S.); (R.A.E.)
| | - Abdelhamied A. Ateya
- Department of Electronics and Communications Engineering, Zagazig University, Zagazig 44519, Egypt; (M.O.); (M.S.S.); (R.A.E.)
- EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia; (M.H.); (A.A.A.E.-L.)
| | - Mohammed S. Sayed
- Department of Electronics and Communications Engineering, Zagazig University, Zagazig 44519, Egypt; (M.O.); (M.S.S.); (R.A.E.)
- Department of Electronics and Communication Engineering, Egypt-Japan University of Science and Technology, Alexandria 21934, Egypt
| | - Mohamed Hammad
- EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia; (M.H.); (A.A.A.E.-L.)
- Department of Information Technology, Faculty of Computers and Information, Menoufia University, Shibin El Kom 32511, Egypt
| | - Paweł Pławiak
- Department of Computer Science, Faculty of Computer Science and Telecommunications, Cracow University of Technology, Warszawska 24, 31-155 Krakow, Poland
- Institute of Theoretical and Applied Informatics, Polish Academy of Sciences, Bałtycka 5, 44-100 Gliwice, Poland
| | - Ahmed A. Abd El-Latif
- EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh 11586, Saudi Arabia; (M.H.); (A.A.A.E.-L.)
- Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Shibin El Kom 32511, Egypt
| | - Rania A. Elsayed
- Department of Electronics and Communications Engineering, Zagazig University, Zagazig 44519, Egypt; (M.O.); (M.S.S.); (R.A.E.)
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Moon KS, Lee SQ. A Wearable Multimodal Wireless Sensing System for Respiratory Monitoring and Analysis. SENSORS (BASEL, SWITZERLAND) 2023; 23:6790. [PMID: 37571572 PMCID: PMC10422350 DOI: 10.3390/s23156790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 07/15/2023] [Accepted: 07/27/2023] [Indexed: 08/13/2023]
Abstract
Wireless sensing systems are required for continuous health monitoring and data collection. It allows for patient data collection in real time rather than through time-consuming and expensive hospital or lab visits. This technology employs wearable sensors, signal processing, and wireless data transfer to remotely monitor patients' health. The research offers a novel approach to providing primary diagnostics remotely with a digital health system for monitoring pulmonary health status using a multimodal wireless sensor device. The technology uses a compact wearable with new integration of acoustics and biopotentials sensors to monitor cardiovascular and respiratory activity to provide comprehensive and fast health status monitoring. Furthermore, the small wearable sensor size may stick to human skin and record heart and lung activities to monitor respiratory health. This paper proposes a sensor data fusion method of lung sounds and cardiograms for potential real-time respiration pattern diagnostics, including respiratory episodes like low tidal volume and coughing. With a p-value of 0.003 for sound signals and 0.004 for electrocardiogram (ECG), preliminary tests demonstrated that it was possible to detect shallow breathing and coughing at a meaningful level.
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Affiliation(s)
- Kee S. Moon
- Department of Mechanical Engineering, San Diego State University, San Diego, CA 92182, USA
| | - Sung Q Lee
- Electronics and Telecommunications Research Institute, Daejeon 34129, Republic of Korea
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Arntz A, Weber F, Handgraaf M, Lällä K, Korniloff K, Murtonen KP, Chichaeva J, Kidritsch A, Heller M, Sakellari E, Athanasopoulou C, Lagiou A, Tzonichaki I, Salinas-Bueno I, Martínez-Bueso P, Velasco-Roldán O, Schulz RJ, Grüneberg C. Technologies in Home-Based Digital Rehabilitation: Scoping Review. JMIR Rehabil Assist Technol 2023; 10:e43615. [PMID: 37253381 PMCID: PMC10415951 DOI: 10.2196/43615] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 03/10/2023] [Accepted: 05/25/2023] [Indexed: 06/01/2023] Open
Abstract
BACKGROUND Due to growing pressure on the health care system, a shift in rehabilitation to home settings is essential. However, efficient support for home-based rehabilitation is lacking. The COVID-19 pandemic has further exacerbated these challenges and has affected individuals and health care professionals during rehabilitation. Digital rehabilitation (DR) could support home-based rehabilitation. To develop and implement DR solutions that meet clients' needs and ease the growing pressure on the health care system, it is necessary to provide an overview of existing, relevant, and future solutions shaping the constantly evolving market of technologies for home-based DR. OBJECTIVE In this scoping review, we aimed to identify digital technologies for home-based DR, predict new or emerging DR trends, and report on the influences of the COVID-19 pandemic on DR. METHODS The scoping review followed the framework of Arksey and O'Malley, with improvements made by Levac et al. A literature search was performed in PubMed, Embase, CINAHL, PsycINFO, and the Cochrane Library. The search spanned January 2015 to January 2022. A bibliometric analysis was performed to provide an overview of the included references, and a co-occurrence analysis identified the technologies for home-based DR. A full-text analysis of all included reviews filtered the trends for home-based DR. A gray literature search supplemented the results of the review analysis and revealed the influences of the COVID-19 pandemic on the development of DR. RESULTS A total of 2437 records were included in the bibliometric analysis and 95 in the full-text analysis, and 40 records were included as a result of the gray literature search. Sensors, robotic devices, gamification, virtual and augmented reality, and digital and mobile apps are already used in home-based DR; however, artificial intelligence and machine learning, exoskeletons, and digital and mobile apps represent new and emerging trends. Advantages and disadvantages were displayed for all technologies. The COVID-19 pandemic has led to an increased use of digital technologies as remote approaches but has not led to the development of new technologies. CONCLUSIONS Multiple tools are available and implemented for home-based DR; however, some technologies face limitations in the application of home-based rehabilitation. However, artificial intelligence and machine learning could be instrumental in redesigning rehabilitation and addressing future challenges of the health care system, and the rehabilitation sector in particular. The results show the need for feasible and effective approaches to implement DR that meet clients' needs and adhere to framework conditions, regardless of exceptional situations such as the COVID-19 pandemic.
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Affiliation(s)
- Angela Arntz
- Division of Physiotherapy, Department of Applied Health Sciences, University of Applied Health Sciences Bochum, Bochum, Germany
- Faculty of Human Sciences, University of Cologne, Cologne, Germany
| | - Franziska Weber
- Division of Physiotherapy, Department of Applied Health Sciences, University of Applied Health Sciences Bochum, Bochum, Germany
- Department of Rehabilitation, Physiotherapy Science & Sports, University Medical Center Utrecht, Utrecht, Netherlands
| | - Marietta Handgraaf
- Division of Physiotherapy, Department of Applied Health Sciences, University of Applied Health Sciences Bochum, Bochum, Germany
| | - Kaisa Lällä
- Institute of Rehabilitation, Jamk University of Applied Sciences, Jyväskylä, Finland
| | - Katariina Korniloff
- Institute of Rehabilitation, Jamk University of Applied Sciences, Jyväskylä, Finland
| | - Kari-Pekka Murtonen
- Institute of Rehabilitation, Jamk University of Applied Sciences, Jyväskylä, Finland
| | - Julija Chichaeva
- Institute of Rehabilitation, Jamk University of Applied Sciences, Jyväskylä, Finland
| | - Anita Kidritsch
- Institute of Health Sciences, St. Pölten University of Applied Sciences, St. Pölten, Austria
| | - Mario Heller
- Department of Media & Digital Technologies, St. Pölten University of Applied Sciences, St. Pölten, Austria
| | - Evanthia Sakellari
- Department of Public and Community Health, Laboratory of Hygiene and Epidemiology, University of West Attica, Athens, Greece
| | | | - Areti Lagiou
- Department of Public and Community Health, Laboratory of Hygiene and Epidemiology, University of West Attica, Athens, Greece
| | - Ioanna Tzonichaki
- Department of Occupational Therapy, University of West Attica, Athens, Greece
| | - Iosune Salinas-Bueno
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
- Department of Nursing and Physiotherapy, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Pau Martínez-Bueso
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
- Department of Nursing and Physiotherapy, University of the Balearic Islands, Palma de Mallorca, Spain
| | - Olga Velasco-Roldán
- Health Research Institute of the Balearic Islands (IdISBa), Palma de Mallorca, Spain
- Department of Nursing and Physiotherapy, University of the Balearic Islands, Palma de Mallorca, Spain
| | | | - Christian Grüneberg
- Division of Physiotherapy, Department of Applied Health Sciences, University of Applied Health Sciences Bochum, Bochum, Germany
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Sánchez-Fernández LP, Sánchez-Pérez LA, Concha-Gómez PD, Shaout A. Kinetic tremor analysis using wearable sensors and fuzzy inference systems in Parkinson's disease. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/27/2023]
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14
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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] [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.
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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
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Davydov R, Zaitceva A, Davydov V, Isakova D, Mazing M. New Methodology of Human Health Express Diagnostics Based on Pulse Wave Measurements and Occlusion Test. J Pers Med 2023; 13:jpm13030443. [PMID: 36983623 PMCID: PMC10052938 DOI: 10.3390/jpm13030443] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 02/24/2023] [Accepted: 02/27/2023] [Indexed: 03/05/2023] Open
Abstract
Nowadays, with the increase in the rhythm of life, the relevance of using express diagnostics methods for human health state estimation has significantly increased. We present a new express diagnostics method based on non-invasive measurements (the pulse wave shape, heart rate, blood pressure, and oxygen saturation of blood vessels and tissues). A feature of these measurements is that they can be carried out both in the hospital and at home. The new compact and portable optical hardware–software complex has been developed to measure tissue oxygen saturation. This complex makes it possible to reduce the measurement time from 60 min to 7–8 min, which reduces the likelihood of artifacts in the measurement process and increases its reliability. A new technique has been developed to carry out these measurements. A new optical sensor based on a line of charge-coupled devices has been developed to register a pulse wave in the far peripheral zone. The developed new technique for processing the pulse waveform and data on the oxygen saturation of hemoglobin in the blood and tissues allows a person to obtain additional information about their state of health independently. It will help to make conclusions about taking the necessary measures. This additional information allows the attending physician to provide more effective control over the course of treatment of the patient at any time since the methods of express diagnostics proposed by us have no restrictions on the number of applications. The functional state of more than 300 patients was studied. The results of various measurements are presented.
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Affiliation(s)
- Roman Davydov
- Institute of Physics and Mechanics, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
- Correspondence:
| | - Anna Zaitceva
- Institute for Analytical Instrumentation of the Russian Academy of Sciences, 190103 St. Petersburg, Russia
- Institute of Biomedical Systems and Biotechnology, Peter the Great, St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
| | - Vadim Davydov
- Institute of Electronics and Telecommunications, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
- Department of Photonics and Communication Lines, The Bonch-Bruevich Saint Petersburg State University of Telecommunication, 193232 St. Petersburg, Russia
| | - Daria Isakova
- Department of Photonics and Communication Lines, The Bonch-Bruevich Saint Petersburg State University of Telecommunication, 193232 St. Petersburg, Russia
| | - Maria Mazing
- Institute for Analytical Instrumentation of the Russian Academy of Sciences, 190103 St. Petersburg, Russia
- Institute of Electronics and Telecommunications, Peter the Great St. Petersburg Polytechnic University, 195251 St. Petersburg, Russia
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Kaczmarek W, Pulik Ł, Łęgosz P, Mucha K. Mobility Analysis of the Lumbar Spine with a Dynamic Spine-Correction Device. SENSORS (BASEL, SWITZERLAND) 2023; 23:1940. [PMID: 36850539 PMCID: PMC9965779 DOI: 10.3390/s23041940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 06/18/2023]
Abstract
According to data, 60-70% of the world's population experience low-back pain (LBP) at least once during their lifetime, often at a young or middle age. Those affected are at risk of having worse quality of life, more missed days at work, and higher medical care costs. We present a new rehabilitation method that helps collect and analyze data on an ongoing basis and offers a more personalized therapeutic approach. This method involves assessing lumbar spine rotation (L1-L5) during torso movement using an innovative dynamic spine correction (DSC) device designed for postural neuromuscular reeducation in LBP. Spinal mobility was tested in 54 patients (aged 18 to 40 years) without LBP. Measurements were made with 12-bit rotary position sensors (AS5304) of the DSC device. During exercise, the mean lumbar spine rotation to the right was greater (4.78° ± 2.24°) than that to the left (2.99° ± 1.44°; p < 0.001). Similarly, the maximum rotation to the right was greater (11.35° ± 3.33°) than that to the left (7.42° ± 1.44°; p < 0.0001). The measurements obtained in the study can serve as a reference for future therapeutic use of the device.
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Affiliation(s)
| | - Łukasz Pulik
- Department of Orthopedics and Traumatology, Medical University of Warsaw, 02-005 Warsaw, Poland
| | - Paweł Łęgosz
- Department of Orthopedics and Traumatology, Medical University of Warsaw, 02-005 Warsaw, Poland
| | - Krzysztof Mucha
- Department of Immunology, Transplantology and Internal Diseases, Medical University of Warsaw, 02-006 Warsaw, Poland
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De Fazio R, Mastronardi VM, De Vittorio M, Visconti P. Wearable Sensors and Smart Devices to Monitor Rehabilitation Parameters and Sports Performance: An Overview. SENSORS (BASEL, SWITZERLAND) 2023; 23:s23041856. [PMID: 36850453 PMCID: PMC9965388 DOI: 10.3390/s23041856] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 05/03/2023]
Abstract
A quantitative evaluation of kinetic parameters, the joint's range of motion, heart rate, and breathing rate, can be employed in sports performance tracking and rehabilitation monitoring following injuries or surgical operations. However, many of the current detection systems are expensive and designed for clinical use, requiring the presence of a physician and medical staff to assist users in the device's positioning and measurements. The goal of wearable sensors is to overcome the limitations of current devices, enabling the acquisition of a user's vital signs directly from the body in an accurate and non-invasive way. In sports activities, wearable sensors allow athletes to monitor performance and body movements objectively, going beyond the coach's subjective evaluation limits. The main goal of this review paper is to provide a comprehensive overview of wearable technologies and sensing systems to detect and monitor the physiological parameters of patients during post-operative rehabilitation and athletes' training, and to present evidence that supports the efficacy of this technology for healthcare applications. First, a classification of the human physiological parameters acquired from the human body by sensors attached to sensitive skin locations or worn as a part of garments is introduced, carrying important feedback on the user's health status. Then, a detailed description of the electromechanical transduction mechanisms allows a comparison of the technologies used in wearable applications to monitor sports and rehabilitation activities. This paves the way for an analysis of wearable technologies, providing a comprehensive comparison of the current state of the art of available sensors and systems. Comparative and statistical analyses are provided to point out useful insights for defining the best technologies and solutions for monitoring body movements. Lastly, the presented review is compared with similar ones reported in the literature to highlight its strengths and novelties.
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Affiliation(s)
- Roberto De Fazio
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
- Facultad de Ingeniería, Universidad Panamericana, Aguascalientes 20290, Mexico
- Correspondence: (R.D.F.); (V.M.M.); Tel.: +39-08-3229-7334 (R.D.F.)
| | - Vincenzo Mariano Mastronardi
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
- Center for Biomolecular Nanotechnologies, Italian Technology Institute IIT, 73010 Arnesano, Italy
- Correspondence: (R.D.F.); (V.M.M.); Tel.: +39-08-3229-7334 (R.D.F.)
| | - Massimo De Vittorio
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
- Center for Biomolecular Nanotechnologies, Italian Technology Institute IIT, 73010 Arnesano, Italy
| | - Paolo Visconti
- Department of Innovation Engineering, University of Salento, 73100 Lecce, Italy
- Center for Biomolecular Nanotechnologies, Italian Technology Institute IIT, 73010 Arnesano, Italy
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Cherry-Allen KM, French MA, Stenum J, Xu J, Roemmich RT. Opportunities for Improving Motor Assessment and Rehabilitation After Stroke by Leveraging Video-Based Pose Estimation. Am J Phys Med Rehabil 2023; 102:S68-S74. [PMID: 36634334 DOI: 10.1097/phm.0000000000002131] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/14/2023]
Abstract
ABSTRACT Stroke is a leading cause of long-term disability in adults in the United States. As the healthcare system moves further into an era of digital medicine and remote monitoring, technology continues to play an increasingly important role in post-stroke care. In this Analysis and Perspective article, opportunities for using human pose estimation-an emerging technology that uses artificial intelligence to track human movement kinematics from simple videos recorded using household devices (e.g., smartphones, tablets)-to improve motor assessment and rehabilitation after stroke are discussed. The focus is on the potential of two key applications: (1) improving access to quantitative, objective motor assessment and (2) advancing telerehabilitation for persons post-stroke.
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Affiliation(s)
- Kendra M Cherry-Allen
- From the Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland (KMC-A, MAF, JS, RTR); Department of Physical Therapy Education, Western University of Health Sciences, Lebanon, Oregon (KMC-A); Center for Movement Studies, Kennedy Krieger Institute, Baltimore, Maryland (JS, RTR); and Department of Kinesiology, University of Georgia, Athens, Georgia (JX)
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Liljeroos M, Arkkukangas M. Implementation of Telemonitoring in Health Care: Facilitators and Barriers for Using eHealth for Older Adults with Chronic Conditions. Risk Manag Healthc Policy 2023; 16:43-53. [PMID: 36647422 PMCID: PMC9840402 DOI: 10.2147/rmhp.s396495] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023] Open
Abstract
Purpose The retrospective study used a hybrid design aimed to a) describe the implementation process of telemonitoring from stakeholders' perspectives and b) identify facilitators and barriers perceived by the care team. Patients and Methods Qualitative interview data were analyzed using manifest inductive qualitative content analysis to describe what was perceived as barriers and what facilitated the implementation. Participating healthcare professionals recruited from a multi-professional care team in Sweden. Overall, 14 healthcare professionals comprising 8 assistant nurses, 3 nurses, 1 physiotherapist, 1 occupational therapist, and one general practitioner participated in five interviews. Results Four categories were derived from the interview analysis: previous experience with digital technology, the need for preparation before implementation, perceptions of using telemonitoring in daily practice from the patient's perspective, and perceptions of the relevance and reasons for applying telemonitoring from the care team's perspective. The identification of stakeholders and the need to plan carefully when proposing the introduction of telemonitoring systems into work practices are both crucial. Conclusion The attitudes of healthcare professionals can be a significant factor in the acceptance and efficiency of the use of telemonitoring in practice. Therefore, implementing new technology in healthcare should involve healthcare professionals at an early stage to gain common understanding.
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Affiliation(s)
- Maria Liljeroos
- Department of Health, Medicine and Caring Sciences, Linköping University, Linköping, Sweden,Centre for Clinical Research Sörmland, Uppsala University, Eskilstuna, Sweden
| | - Marina Arkkukangas
- Centre for Clinical Research Sörmland, Uppsala University, Eskilstuna, Sweden,Department of Medicine and Sport Sciences, School of Health and Welfare, Dalarna University, Falun, Sweden,Department of Physiotherapy, School of Health, Care and Social Welfare, Mälardalen University, Västerås, Sweden,Correspondence: Marina Arkkukangas, Research and Development in Sörmland, Eskilstuna, Sweden, Tel +46 706468868, Email
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Sengchuai K, Kanjanaroat C, Jaruenpunyasak J, Limsakul C, Tayati W, Booranawong A, Jindapetch N. Development of a Real-Time Knee Extension Monitoring and Rehabilitation System: Range of Motion and Surface EMG Measurement and Evaluation. Healthcare (Basel) 2022; 10:healthcare10122544. [PMID: 36554067 PMCID: PMC9778223 DOI: 10.3390/healthcare10122544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/07/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
In this paper, a real-time knee extension monitoring and rehabilitation system for people, such as patients, the elderly, athletes, etc., is developed and tested. The proposed system has three major functions. The first function is two-channel surface electromyography (EMG) signal measurement and processing for the vastus lateralis (VL) and vastus medialis (VM) muscles using a developed EMG device set. The second function is the knee extension range of motion (ROM) measurement using an angle sensor device set (i.e., accelerometer sensor). Both functions are connected and parallelly processed by the NI-myRIO embedded device. Finally, the third function is the graphical user interface (GUI) using LabVIEW, where the knee rehabilitation program can be defined and flexibly set, as recommended by physical therapists and physicians. Experimental results obtained from six healthy subjects demonstrated that the proposed system can efficiently work with real-time response. It can support multiple rehabilitation users with data collection, where EMG signals with mean absolute value (MAV) and root mean square value (RMS) results and knee extension ROM data can be automatically measured and recorded based on the defined rehabilitation program. Furthermore, the proposed system is also employed in the hospital for validation and evaluation, where bio-feedback EMG and ROM data from six patients, including (a) knee osteoarthritis, (b) herniated disc, (c) knee ligament injury, (d) ischemic stroke, (e) hemorrhagic stroke, and (f) Parkinson are obtained. Such data are also collected for one month for tracking, evaluation, and treatment. With our proposed system, results indicate that the rehabilitation people can practice themselves and know their rehabilitation progress during the time of testing. The system can also evaluate (as a primary treatment) whether the therapy training is successful or not, while experts can simultaneously review the progress and set the optimal treatment program in response to the rehabilitation users. This technology can also be integrated as a part of the Internet of Things (IoT) and smart healthcare systems.
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Affiliation(s)
- Kiattisak Sengchuai
- Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla 90110, Thailand
| | - Chinnakrit Kanjanaroat
- Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla 90110, Thailand
| | - Jermphiphut Jaruenpunyasak
- Department of Biomedical Sciences and Biomedical Engineering, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand
| | - Chonnanid Limsakul
- Department of Rehabilitation Medicine, Faculty of Medicine, Prince of Songkla University, Songkhla 90110, Thailand
| | - Watcharin Tayati
- Physical Therapy Unit, Department of Rehabilitation, Trang Hospital, Trang 92000, Thailand
| | - Apidet Booranawong
- Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla 90110, Thailand
| | - Nattha Jindapetch
- Department of Electrical Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla 90110, Thailand
- Correspondence:
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Hamilton RI, Williams J, Holt C. Biomechanics beyond the lab: Remote technology for osteoarthritis patient data-A scoping review. FRONTIERS IN REHABILITATION SCIENCES 2022; 3:1005000. [PMID: 36451804 PMCID: PMC9701737 DOI: 10.3389/fresc.2022.1005000] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 10/05/2022] [Indexed: 01/14/2024]
Abstract
The objective of this project is to produce a review of available and validated technologies suitable for gathering biomechanical and functional research data in patients with osteoarthritis (OA), outside of a traditionally fixed laboratory setting. A scoping review was conducted using defined search terms across three databases (Scopus, Ovid MEDLINE, and PEDro), and additional sources of information from grey literature were added. One author carried out an initial title and abstract review, and two authors independently completed full-text screenings. Out of the total 5,164 articles screened, 75 were included based on inclusion criteria covering a range of technologies in articles published from 2015. These were subsequently categorised by technology type, parameters measured, level of remoteness, and a separate table of commercially available systems. The results concluded that from the growing number of available and emerging technologies, there is a well-established range in use and further in development. Of particular note are the wide-ranging available inertial measurement unit systems and the breadth of technology available to record basic gait spatiotemporal measures with highly beneficial and informative functional outputs. With the majority of technologies categorised as suitable for part-remote use, the number of technologies that are usable and fully remote is rare and they usually employ smartphone software to enable this. With many systems being developed for camera-based technology, such technology is likely to increase in usability and availability as computational models are being developed with increased sensitivities to recognise patterns of movement, enabling data collection in the wider environment and reducing costs and creating a better understanding of OA patient biomechanical and functional movement data.
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Affiliation(s)
- Rebecca I. Hamilton
- Musculoskeletal Biomechanics Research Facility, School of Engineering, Cardiff University, Cardiff, United Kingdom
| | - Jenny Williams
- Musculoskeletal Biomechanics Research Facility, School of Engineering, Cardiff University, Cardiff, United Kingdom
| | | | - Cathy Holt
- Musculoskeletal Biomechanics Research Facility, School of Engineering, Cardiff University, Cardiff, United Kingdom
- Osteoarthritis Technology NetworkPlus (OATech+), EPSRC UK-Wide Research Network+, United Kingdom
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Wilson F, McHugh C, MacManus C, Baggish A, Tanayan C, Reddy S, Wasfy MM, Reilly RB. Diagnostic Accuracy of a Portable ECG Device in Rowing Athletes. Diagnostics (Basel) 2022; 12:diagnostics12102271. [PMID: 36291961 PMCID: PMC9600971 DOI: 10.3390/diagnostics12102271] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Revised: 09/14/2022] [Accepted: 09/18/2022] [Indexed: 11/17/2022] Open
Abstract
Background: Athletes can experience exercise-induced transient arrythmias during high-intensity exercise or competition, which are difficult to capture on traditional Holter monitors or replicate in clinical exercise testing. The aim of this study was to investigate the reliability of a portable single channel ECG sensor and data recorder (PluxECG) and to evaluate the confidence and reliability in interpretation of ECGs recorded using the PluxECG during remote rowing. Methods: This was a two-phase study on rowing athletes. Phase I assessed the accuracy and precision of heart rate (HR) using the PluxECG system compared to a reference 12-lead ECG system. Phase II evaluated the confidence and reliability in interpretation of ECGs during ergometer (ERG) and on-water (OW) rowing at moderate and high intensities. ECGs were reviewed by two expert readers for HR, rhythm, artifact and confidence in interpretation. Results: Findings from Phase I found that 91.9% of samples were within the 95% confidence interval for the instantaneous value of the changing exercising HR. The mean correlation coefficient across participants and tests was 0.9886 (σ = 0.0002, SD = 0.017) and between the two systems at elevated HR was 0.9676 (σ = 0.002, SD = 0.05). Findings from Phase II found significant differences for the presence of artifacts and confidence in interpretation in ECGs between readers’ for both intensities and testing conditions. Interpretation of ECGs for OW rowing had a lower level of reader agreement than ERG rowing for HR, rhythm, and artifact. Using consensus data between readers’ significant differences were apparent between OW and ERG rowing at high-intensity rowing for HR (p = 0.05) and artifact (p = 0.01). ECGs were deemed of moderate-low quality based on confidence in interpretation and the presence of artifacts. Conclusions: The PluxECG device records accurate and reliable HR but not ECG data during exercise in rowers. The quality of ECG tracing derived from the PluxECG device is moderate-low, therefore the confidence in ECG interpretation using the PluxECG device when recorded on open water is inadequate at this time.
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Affiliation(s)
- Fiona Wilson
- Discipline of Physiotherapy, School of Medicine, Trinity College Dublin, D08 W9RT Dublin, Ireland
| | - Cliodhna McHugh
- Discipline of Physiology, School of Medicine, Trinity College Dublin, D02 R590 Dublin, Ireland
- Correspondence:
| | | | - Aaron Baggish
- Cardiovascular Performance Programme, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Christopher Tanayan
- Cardiovascular Performance Programme, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Satyajit Reddy
- Cardiovascular Performance Programme, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Meagan M. Wasfy
- Cardiovascular Performance Programme, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Richard B. Reilly
- Centre for Bioengineering, School of Medicine, Trinity College Dublin, D02 R590 Dublin, Ireland
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Carnevale A, Mannocchi I, Sassi MSH, Carli M, De Luca G, Longo UG, Denaro V, Schena E. Virtual Reality for Shoulder Rehabilitation: Accuracy Evaluation of Oculus Quest 2. SENSORS (BASEL, SWITZERLAND) 2022; 22:s22155511. [PMID: 35898015 PMCID: PMC9332705 DOI: 10.3390/s22155511] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/20/2022] [Accepted: 07/22/2022] [Indexed: 05/14/2023]
Abstract
Virtual reality (VR) systems are becoming increasingly attractive as joint kinematics monitoring systems during rehabilitation. This study aimed to evaluate the accuracy of the Oculus Quest 2 in measuring translational and rotational displacements. As the Oculus Quest 2 was chosen for future applications in shoulder rehabilitation, the translation range (minimum: ~200 mm, maximum: ~700 mm) corresponded to the forearm length of the 5th percentile female and the upper limb length of the 95th percentile male. The controller was moved on two structures designed to allow different translational displacements and rotations in the range 0-180°, to cover the range of motion of the upper limb. The controller measures were compared with those of a Qualisys optical capture system. The results showed a mean absolute error of 13.52 ± 6.57 mm at a distance of 500 mm from the head-mounted display along the x-direction. The maximum mean absolute error for rotational displacements was found to be 1.11 ± 0.37° for a rotation of 40° around the z-axis. Oculus Quest 2 is a promising VR tool for monitoring shoulder kinematics during rehabilitation. The inside-out movement tracking makes Oculus Quest 2 a viable alternative to traditional motion analysis systems.
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Affiliation(s)
- Arianna Carnevale
- Research Unit of Orthopaedic and Trauma Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy; (A.C.); (G.D.L.); (V.D.)
- Research Unit of Orthopaedic and Trauma Surgery, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
- Laboratory of Measurement and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy;
| | - Ilaria Mannocchi
- Department of Industrial, Electronic and Mechanical Engineering, University of Roma Tre, Via Vito Volterra, 62, 00146 Rome, Italy; (I.M.); (M.S.H.S.); (M.C.)
| | - Mohamed Saifeddine Hadj Sassi
- Department of Industrial, Electronic and Mechanical Engineering, University of Roma Tre, Via Vito Volterra, 62, 00146 Rome, Italy; (I.M.); (M.S.H.S.); (M.C.)
| | - Marco Carli
- Department of Industrial, Electronic and Mechanical Engineering, University of Roma Tre, Via Vito Volterra, 62, 00146 Rome, Italy; (I.M.); (M.S.H.S.); (M.C.)
| | - Giovanna De Luca
- Research Unit of Orthopaedic and Trauma Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy; (A.C.); (G.D.L.); (V.D.)
- Research Unit of Orthopaedic and Trauma Surgery, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
- Laboratory of Measurement and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy;
| | - Umile Giuseppe Longo
- Research Unit of Orthopaedic and Trauma Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy; (A.C.); (G.D.L.); (V.D.)
- Research Unit of Orthopaedic and Trauma Surgery, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
- Correspondence:
| | - Vincenzo Denaro
- Research Unit of Orthopaedic and Trauma Surgery, Fondazione Policlinico Universitario Campus Bio-Medico, Via Alvaro del Portillo, 200, 00128 Roma, Italy; (A.C.); (G.D.L.); (V.D.)
- Research Unit of Orthopaedic and Trauma Surgery, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Roma, Italy
| | - Emiliano Schena
- Laboratory of Measurement and Biomedical Instrumentation, Department of Engineering, Università Campus Bio-Medico di Roma, Via Alvaro del Portillo, 21, 00128 Rome, Italy;
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Wearable Sensors for Vital Signs Measurement: A Survey. JOURNAL OF SENSOR AND ACTUATOR NETWORKS 2022. [DOI: 10.3390/jsan11010019] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
With the outbreak of coronavirus disease-2019 (COVID-19) worldwide, developments in the medical field have aroused concerns within society. As science and technology develop, wearable medical sensors have become the main means of medical data acquisition. To analyze the intelligent development status of wearable medical sensors, the current work classifies and prospects the application status and functions of wireless communication wearable medical sensors, based on human physiological data acquisition in the medical field. By understanding its working principles, data acquisition modes and action modes, the work chiefly analyzes the application of wearable medical sensors in vascular infarction, respiratory intensity, body temperature, blood oxygen concentration, and sleep detection, and reflects the key role of wearable medical sensors in human physiological data acquisition. Further exploration and prospecting are made by investigating the improvement of information security performance of wearable medical sensors, the improvement of biological adaptability and biodegradability of new materials, and the integration of wearable medical sensors and intelligence-assisted rehabilitation. The research expects to provide a reference for the intelligent development of wearable medical sensors and real-time monitoring of human health in the follow-up medical field.
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French MA, Roemmich RT, Daley K, Beier M, Penttinen S, Raghavan P, Searson P, Wegener S, Celnik P. Precision rehabilitation: optimizing function, adding value to health care. Arch Phys Med Rehabil 2022; 103:1233-1239. [PMID: 35181267 DOI: 10.1016/j.apmr.2022.01.154] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 01/07/2022] [Accepted: 01/31/2022] [Indexed: 12/12/2022]
Abstract
Precision medicine efforts are underway in many medical disciplines; however, the power of precision rehabilitation has not yet been explored. Precision medicine aims to deliver the right intervention, at the right time, in the right setting, for the right person, ultimately, bolstering the value of the care that we provide. To date precision medicine efforts have rarely focused on function at the level of a person, but precision rehabilitation is poised to change this and bring the focus on function to the broader precision medicine enterprise. To do this, subgroups of individuals must be identified based on their level of function via precise measurement of their abilities in the physical, cognitive, and psychosocial domains. Adoption of electronic health records, advances in data storage and analytics, and improved measurement technology make this shift possible. Here we detail critical components of the precision rehabilitation framework, including 1) the synergistic use of various study designs, 2) the need for standardized functional measurements, 3) the importance of precise and longitudinal measures of function, 4) the utility of comprehensive databases, 5) the importance of predictive analyses, and 6) the need for system and team science. Precision rehabilitation has the potential to revolutionize clinical care, optimize function for all individuals, and magnify the value of rehabilitation in healthcare; however, to reap the benefits of precision rehabilitation, the rehabilitation community must actively pursue this shift.
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Affiliation(s)
- Margaret A French
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Ryan T Roemmich
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America; Kennedy Krieger Institute, Center for Movement Studies, Baltimore, Maryland, United States of America
| | - Kelly Daley
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Meghan Beier
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Sharon Penttinen
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America; Kennedy Krieger Institute, Center for Movement Studies, Baltimore, Maryland, United States of America; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America; Institute of Nanobiotechnology, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Preeti Raghavan
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Peter Searson
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States of America; Institute of Nanobiotechnology, Johns Hopkins University, Baltimore, Maryland, United States of America
| | - Stephen Wegener
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Pablo Celnik
- Department of Physical Medicine and Rehabilitation, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America.
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Bhardwaj V, Joshi R, Gaur AM. IoT-Based Smart Health Monitoring System for COVID-19. SN COMPUTER SCIENCE 2022; 3:137. [PMID: 35079705 PMCID: PMC8772261 DOI: 10.1007/s42979-022-01015-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Accepted: 01/03/2022] [Indexed: 11/29/2022]
Abstract
With the commencement of the COVID-19 pandemic, social distancing and quarantine are becoming essential practices in the world. IoT health monitoring systems prevent frequent visits to doctors and meetings between patients and medical professionals. However, many individuals require regular health monitoring and observation through medical staff. In this proposed work, we have taken advantage of the technology to make patients life easier for earlier diagnosis and treatment. A smart health monitoring system is being developed using Internet of Things (IoT) technology which is capable of monitoring blood pressure, heart rate, oxygen level, and temperature of a person. This system is helpful for rural areas or villages where nearby clinics can be in touch with city hospitals about their patient health conditions. However, if any changes occur in a patient's health based on standard values, then the IoT system will alert the physician or doctor accordingly. The maximum relative error (%ϵ r) in the measurement of heart rate, patient body temperature and SPO2 was found to be 2.89%, 3.03%, 1.05%, respectively, which was comparable to the commercials health monitoring system. This health monitoring system based on IoT helps out doctors to collect real-time data effortlessly. The availability of high-speed internet allows the system to monitor the parameters at regular intervals. Furthermore, the cloud platform allows data storage so that previous measurements could be retrieved in the near future. This system would help in identifying and early treatment of COVID-19 individual patients.
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Affiliation(s)
- Vaneeta Bhardwaj
- Department of Electronics and Communication Engineering, ADESH Institute of Technology, Mohali, Punjab India
| | - Rajat Joshi
- Department of Electronics and Communication Engineering, ADESH Institute of Technology, Mohali, Punjab India
| | - Anshu Mli Gaur
- Electrical and Instrumentation Engineering Department (EIED), Thapar Institute of Engineering and Technology, Patiala, India
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Timmermann C, Ursin F, Predel C, Steger F. Aligning Patient's Ideas of a Good Life with Medically Indicated Therapies in Geriatric Rehabilitation Using Smart Sensors. SENSORS 2021; 21:s21248479. [PMID: 34960570 PMCID: PMC8709340 DOI: 10.3390/s21248479] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/28/2021] [Revised: 12/15/2021] [Accepted: 12/16/2021] [Indexed: 11/16/2022]
Abstract
New technologies such as smart sensors improve rehabilitation processes and thereby increase older adults’ capabilities to participate in social life, leading to direct physical and mental health benefits. Wearable smart sensors for home use have the additional advantage of monitoring day-to-day activities and thereby identifying rehabilitation progress and needs. However, identifying and selecting rehabilitation priorities is ethically challenging because physicians, therapists, and caregivers may impose their own personal values leading to paternalism. Therefore, we develop a discussion template consisting of a series of adaptable questions for the patient–physician encounter based on the capability approach. The goal is to improve geriatric rehabilitation and thereby increase participation in social life and well-being. To achieve this goal, we first analyzed what is considered important for participation on basis of the capability approach, human rights, and ethics of care. Second, we conducted an ethical analysis of each of the four identified dimensions of participation: political, economic, socio-cultural, and care. To improve compliance with rehabilitation measures, health professionals must align rehabilitation measures in an open dialogue with the patient’s aspiration for participation in each dimension. A discussion template based on the capability approach allows for a proactive approach in patient information and stimulates a critical assessment of treatment alternatives while reducing the risk of imposing personal values.
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Affiliation(s)
- Cristian Timmermann
- Institute of the History, Philosophy and Ethics of Medicine, Ulm University, 89073 Ulm, Germany; (C.P.); (F.S.)
- Correspondence:
| | - Frank Ursin
- Institute for Ethics, History and Philosophy of Medicine, Hannover Medical School, 30167 Hannover, Germany;
| | - Christopher Predel
- Institute of the History, Philosophy and Ethics of Medicine, Ulm University, 89073 Ulm, Germany; (C.P.); (F.S.)
| | - Florian Steger
- Institute of the History, Philosophy and Ethics of Medicine, Ulm University, 89073 Ulm, Germany; (C.P.); (F.S.)
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28
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Palumbo A, Vizza P, Calabrese B, Ielpo N. Biopotential Signal Monitoring Systems in Rehabilitation: A Review. SENSORS 2021; 21:s21217172. [PMID: 34770477 PMCID: PMC8587479 DOI: 10.3390/s21217172] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 10/21/2021] [Accepted: 10/25/2021] [Indexed: 12/14/2022]
Abstract
Monitoring physical activity in medical and clinical rehabilitation, in sports environments or as a wellness indicator is helpful to measure, analyze and evaluate physiological parameters involving the correct subject’s movements. Thanks to integrated circuit (IC) technologies, wearable sensors and portable devices have expanded rapidly in monitoring physical activities in sports and tele-rehabilitation. Therefore, sensors and signal acquisition devices became essential in the tele-rehabilitation path to obtain accurate and reliable information by analyzing the acquired physiological signals. In this context, this paper provides a state-of-the-art review of the recent advances in electroencephalogram (EEG), electrocardiogram (ECG) and electromyogram (EMG) signal monitoring systems and sensors that are relevant to the field of tele-rehabilitation and health monitoring. Mostly, we focused our contribution in EMG signals to highlight its importance in rehabilitation context applications. This review focuses on analyzing the implementation of sensors and biomedical applications both in literature than in commerce. Moreover, a final review discussion about the analyzed solutions is also reported at the end of this paper to highlight the advantages of physiological monitoring systems in rehabilitation and individuate future advancements in this direction. The main contributions of this paper are (i) the presentation of interesting works in the biomedical area, mainly focusing on sensors and systems for physical rehabilitation and health monitoring between 2016 and up-to-date, and (ii) the indication of the main types of commercial sensors currently being used for biomedical applications.
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Affiliation(s)
- Arrigo Palumbo
- Department of Medical and Surgical Sciences, Magna Græcia University, 88100 Catanzaro, Italy; (A.P.); (B.C.); (N.I.)
| | - Patrizia Vizza
- Mater Domini University Hospital, 88100 Catanzaro, Italy
- Interdepartmental Center of Services (CIS), Magna Græcia University, 88100 Catanzaro, Italy
- Correspondence:
| | - Barbara Calabrese
- Department of Medical and Surgical Sciences, Magna Græcia University, 88100 Catanzaro, Italy; (A.P.); (B.C.); (N.I.)
| | - Nicola Ielpo
- Department of Medical and Surgical Sciences, Magna Græcia University, 88100 Catanzaro, Italy; (A.P.); (B.C.); (N.I.)
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29
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Ko ST, Asplund F, Zeybek B. A Scoping Review of Pressure Measurements in Prosthetic Sockets of Transfemoral Amputees during Ambulation: Key Considerations for Sensor Design. SENSORS 2021; 21:s21155016. [PMID: 34372253 PMCID: PMC8347332 DOI: 10.3390/s21155016] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 07/11/2021] [Accepted: 07/14/2021] [Indexed: 02/05/2023]
Abstract
Sensor systems to measure pressure at the stump–socket interface of transfemoral amputees are receiving increasing attention as they allow monitoring to evaluate patient comfort and socket fit. However, transfemoral amputees have many unique characteristics, and it is unclear whether existing research on sensor systems take these sufficiently into account or if it is conducted in ways likely to lead to substantial breakthroughs. This investigation addresses these concerns through a scoping review to profile research regarding sensors in transfemoral sockets with the aim of advancing and improving prosthetic socket design, comfort and fit for transfemoral amputees. Publications found from searching four scientific databases were screened, and 17 papers were found relating to the aim of this review. After quality assessment, 12 articles were finally selected for analysis. Three main contributions are provided: a de facto methodology for experimental studies on the implications of intra-socket pressure sensor use for transfemoral amputees; the suggestion that associated sensor design breakthroughs would be more likely if pressure sensors were developed in close combination with other types of sensors and in closer cooperation with those in possession of an in-depth domain knowledge in prosthetics; and that this research would be facilitated by increased interdisciplinary cooperation and open research data generation.
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Affiliation(s)
- Siu-Teing Ko
- Research and Innovation, Össur, 110 Reykjavík, Iceland
- Correspondence:
| | - Fredrik Asplund
- Department of Machine Design, KTH Royal Institute of Technology, 10044 Stockholm, Sweden;
| | - Begum Zeybek
- Healthcare Innovation Centre, School of Health and Life Sciences, Teesside University, Middlesbrough TS1 3BX, UK;
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30
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Flury D, Massé F, Paraschiv-Ionescu A, Aminian K, Luft AR, Gonzenbach R. Clinical value of assessing motor performance in postacute stroke patients. J Neuroeng Rehabil 2021; 18:102. [PMID: 34167546 PMCID: PMC8223372 DOI: 10.1186/s12984-021-00898-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 06/14/2021] [Indexed: 01/28/2023] Open
Abstract
Background Rehabilitative treatment plans after stroke are based on clinical examinations of functional capacity and patient-reported outcomes. Objective information about daily life performance is usually not available, but it may improve therapy personalization. Objective To show that sensor-derived information about daily life performance is clinically valuable for counseling and the planning of rehabilitation programs for individual stroke patients who live at home. Performance information is clinically valuable if it can be used as a decision aid for the therapeutic management or counseling of individual patients. Methods This was an observational, cross-sectional case series including 15 ambulatory stroke patients. Motor performance in daily life was assessed with body-worn inertial sensors attached to the wrists, shanks and trunk that estimated basic physical activity and various measures of walking and arm activity in daily life. Stroke severity, motor function and activity, and degree of independence were quantified clinically by standard assessments and patient-reported outcomes. Motor performance was recorded for an average of 5.03 ± 1.1 h on the same day as the clinical assessment. The clinical value of performance information is explored in a narrative style by considering individual patient performance and capacity information. Results The patients were aged 59.9 ± 9.8 years (mean ± SD), were 6.5 ± 7.2 years post stroke, and had a National Institutes of Health Stroke Score of 4.0 ± 2.6. Capacity and performance measures showed high variability. There were substantial discrepancies between performance and capacity measures in some patients. Conclusions This case series shows that information about motor performance in daily life can be valuable for tailoring rehabilitative therapy plans and counseling according to the needs of individual stroke patients. Although the short recording time (average of 5.03 h) limited the scope of the conclusions, this study highlights the usefulness of objective measures of daily life performance for the planning of rehabilitative therapies. Further research is required to investigate whether information about performance in daily life leads to improved rehabilitative therapy results.
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Affiliation(s)
- D Flury
- Faculty of Medicine, University of Zurich, Zurich, Switzerland.
| | - F Massé
- Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - A Paraschiv-Ionescu
- Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - K Aminian
- Laboratory of Movement Analysis and Measurement, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - A R Luft
- Department of Neurology, University Hospital of Zurich, Zurich, Switzerland.,Center for Neurology and Rehabilitation, Cereneo, Vitznau, Switzerland
| | - R Gonzenbach
- Department of Neurology, University Hospital of Zurich, Zurich, Switzerland
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31
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Knezić Ž, Penava Ž, Penava DŠ, Rogale D. The Impact of Elongation on Change in Electrical Resistance of Electrically Conductive Yarns Woven into Fabric. MATERIALS 2021; 14:ma14123390. [PMID: 34207430 PMCID: PMC8235346 DOI: 10.3390/ma14123390] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/02/2021] [Revised: 06/10/2021] [Accepted: 06/14/2021] [Indexed: 01/11/2023]
Abstract
Electrically conductive yarns (ECYs) are gaining increasing applications in woven textile materials, especially in woven sensors suitable for incorporation into clothing. In this paper, the effect of the yarn count of ECYs woven into fabric on values of electrical resistance is analyzed. We also observe how the direction of action of elongation force, considering the position of the woven ECY, effects the change in the electrical resistance of the electrically conductive fabric. The measurements were performed on nine different samples of fabric in a plain weave, into which were woven ECYs with three different yarn counts and three different directions. Relationship curves between values of elongation forces and elongation to break, as well as relationship curves between values of electrical resistance of fabrics with ECYs and elongation, were experimentally obtained. An analytical mathematical model was also established, and analysis was conducted, which determined the models of function of connection between force and elongation, and between electrical resistance and elongation. The connection between the measurement results and the mathematical model was confirmed. The connection between the mathematical model and the experimental results enables the design of ECY properties in woven materials, especially textile force and elongation sensors.
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Affiliation(s)
- Željko Knezić
- Department of Textile Design and Management, Faculty of Textile Technology, University of Zagreb, 10000 Zagreb, Croatia; (Ž.K.); (Ž.P.)
| | - Željko Penava
- Department of Textile Design and Management, Faculty of Textile Technology, University of Zagreb, 10000 Zagreb, Croatia; (Ž.K.); (Ž.P.)
| | - Diana Šimić Penava
- Department of Engineering Mechanics, Faculty of Civil Engineering, University of Zagreb, 10000 Zagreb, Croatia;
| | - Dubravko Rogale
- Department of Clothing Technology, Faculty of Textile Technology, University of Zagreb, 10000 Zagreb, Croatia
- Correspondence:
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A Novel mHealth Monitoring System during Cycling in Elite Athletes. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2021; 18:ijerph18094788. [PMID: 33946166 PMCID: PMC8124243 DOI: 10.3390/ijerph18094788] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Revised: 04/24/2021] [Accepted: 04/26/2021] [Indexed: 02/04/2023]
Abstract
Background: Cycling is a very demanding physical activity that may create various health disorders during an athlete’s career. Recently, smart mobile and wearable technologies have been used to monitor physiological responses and possible disturbances during physical activity. Thus, the application of mHealth methods in sports poses a challenge today. This study used a novel mobile-Health method to monitor athletes’ physiological responses and to detect health disorders early during cycling in elite athletes. Methods: Sixteen high-level cyclists participated in this study, which included a series of measurements in the laboratory; health and performance assessments; and then application in the field of mHealth monitoring in two training seasons, at the beginning of their training period and in the race season. A field monitoring test took place during 30 min of uphill cycling with the participant’s heart rate at the ventilatory threshold. During monitoring periods, heart rate, oxygen saturation, respiratory rate, and electrocardiogram were monitored via the mHealth system. Moreover, the SpO2 was estimated continuously, and the symptoms during effort were reported. Results: A significant correlation was found between the symptoms reported by the athletes in the two field tests and the findings recorded with the application of the mHealth monitoring method. However, from the pre-participation screening in the laboratory and from the spiroergometric tests, no abnormal findings were detected that were to blame for the appearance of the symptoms. Conclusions: The application of mHealth monitoring during competitive cycling is a very useful method for the early recording of cardiac and other health disorders of athletes, whose untimely evaluation could lead to unforeseen events.
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Minimum Mapping from EMG Signals at Human Elbow and Shoulder Movements into Two DoF Upper-Limb Robot with Machine Learning. MACHINES 2021. [DOI: 10.3390/machines9030056] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
This research focuses on the minimum process of classifying three upper arm movements (elbow extension, shoulder extension, combined shoulder and elbow extension) of humans with three electromyography (EMG) signals, to control a 2-degrees of freedom (DoF) robotic arm. The proposed minimum process consists of four parts: time divisions of data, Teager–Kaiser energy operator (TKEO), the conventional EMG feature extraction (i.e., the mean absolute value (MAV), zero crossings (ZC), slope-sign changes (SSC), and waveform length (WL)), and eight major machine learning models (i.e., decision tree (medium), decision tree (fine), k-Nearest Neighbor (KNN) (weighted KNN, KNN (fine), Support Vector Machine (SVM) (cubic and fine Gaussian SVM), Ensemble (bagged trees and subspace KNN). Then, we compare and investigate 48 classification models (i.e., 47 models are proposed, and 1 model is the conventional) based on five healthy subjects. The results showed that all the classification models achieved accuracies ranging between 74–98%, and the processing speed is below 40 ms and indicated acceptable controller delay for robotic arm control. Moreover, we confirmed that the classification model with no time division, with TKEO, and with ensemble (subspace KNN) had the best performance in accuracy rates at 96.67, recall rates at 99.66, and precision rates at 96.99. In short, the combination of the proposed TKEO and ensemble (subspace KNN) plays an important role to achieve the EMG classification.
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George UZ, Moon KS, Lee SQ. Extraction and Analysis of Respiratory Motion Using a Comprehensive Wearable Health Monitoring System. SENSORS (BASEL, SWITZERLAND) 2021; 21:1393. [PMID: 33671202 PMCID: PMC7923104 DOI: 10.3390/s21041393] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 02/12/2021] [Accepted: 02/13/2021] [Indexed: 12/22/2022]
Abstract
Respiratory activity is an important vital sign of life that can indicate health status. Diseases such as bronchitis, emphysema, pneumonia and coronavirus cause respiratory disorders that affect the respiratory systems. Typically, the diagnosis of these diseases is facilitated by pulmonary auscultation using a stethoscope. We present a new attempt to develop a lightweight, comprehensive wearable sensor system to monitor respiration using a multi-sensor approach. We employed new wearable sensor technology using a novel integration of acoustics and biopotentials to monitor various vital signs on two volunteers. In this study, a new method to monitor lung function, such as respiration rate and tidal volume, is presented using the multi-sensor approach. Using the new sensor, we obtained lung sound, electrocardiogram (ECG), and electromyogram (EMG) measurements at the external intercostal muscles (EIM) and at the diaphragm during breathing cycles with 500 mL, 625 mL, 750 mL, 875 mL, and 1000 mL tidal volume. The tidal volumes were controlled with a spirometer. The duration of each breathing cycle was 8 s and was timed using a metronome. For each of the different tidal volumes, the EMG data was plotted against time and the area under the curve (AUC) was calculated. The AUC calculated from EMG data obtained at the diaphragm and EIM represent the expansion of the diaphragm and EIM respectively. AUC obtained from EMG data collected at the diaphragm had a lower variance between samples per tidal volume compared to those monitored at the EIM. Using cubic spline interpolation, we built a model for computing tidal volume from EMG data at the diaphragm. Our findings show that the new sensor can be used to measure respiration rate and variations thereof and holds potential to estimate tidal lung volume from EMG measurements obtained from the diaphragm.
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Affiliation(s)
- Uduak Z. George
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA;
| | - Kee S. Moon
- Department of Mechanical Engineering, San Diego State University, San Diego, CA 92182, USA
| | - Sung Q. Lee
- Electronics and Telecommunications Research Institute, Daejeon 34129, Korea;
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Romero Avila E, Junker E, Disselhorst-Klug C. Introduction of a sEMG Sensor System for Autonomous Use by Inexperienced Users. SENSORS (BASEL, SWITZERLAND) 2020; 20:E7348. [PMID: 33371409 PMCID: PMC7767446 DOI: 10.3390/s20247348] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/20/2020] [Revised: 12/15/2020] [Accepted: 12/18/2020] [Indexed: 12/15/2022]
Abstract
Wearable devices play an increasing role in the rehabilitation of patients with movement disorders. Although information about muscular activation is highly interesting, no approach exists that allows reliable collection of this information when the sensor is applied autonomously by the patient. This paper aims to demonstrate the proof-of-principle of an innovative sEMG sensor system, which can be used intuitively by patients while detecting their muscular activation with sufficient accuracy. The sEMG sensor system utilizes a multichannel approach based on 16 sEMG leads arranged circularly around the limb. Its design enables a stable contact between the skin surface and the system's dry electrodes, fulfills the SENIAM recommendations regarding the electrode size and inter-electrode distance and facilitates a high temporal resolution. The proof-of-principle was demonstrated by elbow flexion/extension movements of 10 subjects, proving that it has root mean square values and a signal-to-noise ratio comparable to commercial systems based on pre-gelled electrodes. Furthermore, it can be easily placed and removed by patients with reduced arm function and without detailed knowledge about the exact positioning of the sEMG electrodes. With its features, the demonstration of the sEMG sensor system's proof-of-principle positions it as a wearable device that has the potential to monitor muscular activation in home and community settings.
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Affiliation(s)
| | | | - Catherine Disselhorst-Klug
- Department of Rehabilitation & Prevention Engineering, Institute of Applied Medical Engineering, RWTH Aachen University, Pauwelsstr. 20, 52074 Aachen, Germany; (E.R.A.); (E.J.)
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Kintzios S. Bioelectric Sensors: On the Road for the 4.0 Diagnostics and Biomedtech Revolution. BIOSENSORS-BASEL 2020; 10:bios10080096. [PMID: 32796701 PMCID: PMC7460287 DOI: 10.3390/bios10080096] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 08/04/2020] [Indexed: 02/03/2023]
Affiliation(s)
- Spyridon Kintzios
- Laboratory of Cell Technology, Faculty of Biotechnology, Agricultural University of Athens/EU-CONEXUS European University, 11855 Athens, Greece
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