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Francisco L, Duarte J, Godinho AN, Zdravevski E, Albuquerque C, Pires IM, Coelho PJ. Sensor-based systems for the measurement of Functional Reach Test results: a systematic review. PeerJ Comput Sci 2024; 10:e1823. [PMID: 38660214 PMCID: PMC11042010 DOI: 10.7717/peerj-cs.1823] [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: 07/14/2023] [Accepted: 12/26/2023] [Indexed: 04/26/2024]
Abstract
The measurement of Functional Reach Test (FRT) is a widely used assessment tool in various fields, including physical therapy, rehabilitation, and geriatrics. This test evaluates a person's balance, mobility, and functional ability to reach forward while maintaining stability. Recently, there has been a growing interest in utilizing sensor-based systems to objectively and accurately measure FRT results. This systematic review was performed in various scientific databases or publishers, including PubMed Central, IEEE Explore, Elsevier, Springer, the Multidisciplinary Digital Publishing Institute (MDPI), and the Association for Computing Machinery (ACM), and considered studies published between January 2017 and October 2022, related to methods for the automation of the measurement of the Functional Reach Test variables and results with sensors. Camera-based devices and motion-based sensors are used for Functional Reach Tests, with statistical models extracting meaningful information. Sensor-based systems offer several advantages over traditional manual measurement techniques, as they can provide objective and precise measurements of the reach distance, quantify postural sway, and capture additional parameters related to the movement.
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Affiliation(s)
- Luís Francisco
- School of Technology and Management, Polytechnic University of Leiria, Leiria, Portugal
| | - João Duarte
- School of Technology and Management, Polytechnic University of Leiria, Leiria, Portugal
| | | | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University of Sts. Cyril and Methodius, Skopje, North Macedonia
| | - Carlos Albuquerque
- Child Studies Research Center (CIEC), University of Minho, Braga, Portugal
- Higher School of Health, Polytechnic Institute of Viseu, Viseu, Portugal
- Nursing School of Coimbra (ESEnfC), Health Sciences Research Unit: Nursing (UICISA: E), Coimbra, Portugal
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, Águeda, Portugal
| | - Paulo Jorge Coelho
- School of Technology and Management, Polytechnic University of Leiria, Leiria, Portugal
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), Coimbra, Portugal
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Francisco L, Duarte J, Albuquerque C, Albuquerque D, Pires IM, Coelho PJ. Mobile Data Gathering and Preliminary Analysis for the Functional Reach Test. SENSORS (BASEL, SWITZERLAND) 2024; 24:1301. [PMID: 38400459 PMCID: PMC10892343 DOI: 10.3390/s24041301] [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: 12/15/2023] [Revised: 02/11/2024] [Accepted: 02/15/2024] [Indexed: 02/25/2024]
Abstract
The functional reach test (FRT) is a clinical tool used to evaluate dynamic balance and fall risk in older adults and those with certain neurological diseases. It provides crucial information for developing rehabilitation programs to improve balance and reduce fall risk. This paper aims to describe a new tool to gather and analyze the data from inertial sensors to allow automation and increased reliability in the future by removing practitioner bias and facilitating the FRT procedure. A new tool for gathering and analyzing data from inertial sensors has been developed to remove practitioner bias and streamline the FRT procedure. The study involved 54 senior citizens using smartphones with sensors to execute FRT. The methods included using a mobile app to gather data, using sensor-fusion algorithms like the Madgwick algorithm to estimate orientation, and attempting to estimate location by twice integrating accelerometer data. However, accurate position estimation was difficult, highlighting the need for more research and development. The study highlights the benefits and drawbacks of automated balance assessment testing with mobile device sensors, highlighting the potential of technology to enhance conventional health evaluations.
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Affiliation(s)
- Luís Francisco
- Electrotechnical Department, Polytechnic University of Leiria, 2411-901 Leiria, Portugal
| | - João Duarte
- Electrotechnical Department, Polytechnic University of Leiria, 2411-901 Leiria, Portugal
| | - Carlos Albuquerque
- Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), 3004-011 Coimbra, Portugal;
- Higher School of Health, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal
- Child Studies Research Center (CIEC), University of Minho, 4710-057 Braga, Portugal
| | - Daniel Albuquerque
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, 3750-127 Águeda, Portugal; (D.A.); (I.M.P.)
| | - Ivan Miguel Pires
- Instituto de Telecomunicações, Escola Superior de Tecnologia e Gestão de Águeda, Universidade de Aveiro, 3750-127 Águeda, Portugal; (D.A.); (I.M.P.)
| | - Paulo Jorge Coelho
- Electrotechnical Department, Polytechnic University of Leiria, 2411-901 Leiria, Portugal
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), 3030-290 Coimbra, Portugal
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Szabo DA, Neagu N, Teodorescu S, Apostu M, Predescu C, Pârvu C, Veres C. The Role and Importance of Using Sensor-Based Devices in Medical Rehabilitation: A Literature Review on the New Therapeutic Approaches. SENSORS (BASEL, SWITZERLAND) 2023; 23:8950. [PMID: 37960649 PMCID: PMC10648494 DOI: 10.3390/s23218950] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Revised: 10/22/2023] [Accepted: 10/31/2023] [Indexed: 11/15/2023]
Abstract
Due to the growth of sensor technology, more affordable integrated circuits, and connectivity technologies, the usage of wearable equipment and sensing devices for monitoring physical activities, whether for wellness, sports monitoring, or medical rehabilitation, has exploded. The current literature review was performed between October 2022 and February 2023 using PubMed, Web of Science, and Scopus in accordance with P.R.I.S.M.A. criteria. The screening phase resulted in the exclusion of 69 articles that did not fit the themes developed in all subchapters of the study, 41 articles that dealt exclusively with rehabilitation and orthopaedics, 28 articles whose abstracts were not visible, and 10 articles that dealt exclusively with other sensor-based devices and not medical ones; the inclusion phase resulted in the inclusion of 111 articles. Patients who utilise sensor-based devices have several advantages due to rehabilitating a missing component, which marks the accomplishment of a fundamental goal within the rehabilitation program. As technology moves faster and faster forward, the field of medical rehabilitation has to adapt to the time we live in by using technology and intelligent devices. This means changing every part of rehabilitation and finding the most valuable and helpful gadgets that can be used to regain lost functions, keep people healthy, or prevent diseases.
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Affiliation(s)
- Dan Alexandru Szabo
- Department of Human Movement Sciences, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540139 Targu Mures, Romania;
- Department ME1, Faculty of Medicine in English, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540139 Targu Mures, Romania
| | - Nicolae Neagu
- Department of Human Movement Sciences, George Emil Palade University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 540139 Targu Mures, Romania;
| | - Silvia Teodorescu
- Department of Doctoral Studies, National University of Physical Education and Sports, 060057 Bucharest, Romania;
| | - Mihaela Apostu
- Department of Special Motor and Rehabilitation Medicine, National University of Physical Education and Sports, 060057 Bucharest, Romania; (M.A.); (C.P.)
| | - Corina Predescu
- Department of Special Motor and Rehabilitation Medicine, National University of Physical Education and Sports, 060057 Bucharest, Romania; (M.A.); (C.P.)
| | - Carmen Pârvu
- Faculty of Physical Education and Sports, “Dunărea de Jos” University, 63-65 Gării Street, 337347 Galati, Romania;
| | - Cristina Veres
- Department of Industrial Engineering and Management, University of Medicine, Pharmacy, Science and Technology of Targu Mures, 540142 Targu Mures, Romania;
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Pimenta L, Garcia NM, Zdravevski E, Chorbev I, Trajkovik V, Lameski P, Albuquerque C, Pires IM. Can the Eight Hop Test Be Measured with Sensors? A Systematic Review. SENSORS 2022; 22:s22093582. [PMID: 35591272 PMCID: PMC9105795 DOI: 10.3390/s22093582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/04/2022] [Accepted: 05/06/2022] [Indexed: 02/01/2023]
Abstract
Rehabilitation aims to increase the independence and physical function after injury, surgery, or other trauma, so that patients can recover to their previous ability as much as possible. To be able to measure the degree of recovery and impact of the treatment, various functional performance tests are used. The Eight Hop Test is a hop exercise that is directly linked to the rehabilitation of people suffering from tendon and ligament injuries on the lower limb. This paper presents a systematic review on the use of sensors for measuring functional movements during the execution of the Eight Hop Test, focusing primarily on the use of sensors, related diseases, and different methods implemented. Firstly, an automated search was performed on the publication databases: PubMed, Springer, ACM, IEEE Xplore, MDPI, and Elsevier. Secondly, the publications related to the Eight-Hop Test and sensors were filtered according to several search criteria and 15 papers were finally selected to be analyzed in detail. Our analysis found that the Eight Hop Test measurements can be performed with motion, force, and imaging sensors.
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Affiliation(s)
- Luís Pimenta
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal;
| | - Nuno M. Garcia
- Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal;
| | - Eftim Zdravevski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia; (E.Z.); (I.C.); (V.T.); (P.L.)
| | - Ivan Chorbev
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia; (E.Z.); (I.C.); (V.T.); (P.L.)
| | - Vladimir Trajkovik
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia; (E.Z.); (I.C.); (V.T.); (P.L.)
| | - Petre Lameski
- Faculty of Computer Science and Engineering, University Ss Cyril and Methodius, 1000 Skopje, North Macedonia; (E.Z.); (I.C.); (V.T.); (P.L.)
| | - Carlos Albuquerque
- Health Sciences Research Unit: Nursing (UICISA: E), Nursing School of Coimbra (ESEnfC), 3046-851 Coimbra, Portugal;
- Higher School of Health, Polytechnic Institute of Viseu, 3504-510 Viseu, Portugal
- Child Studies Research Center (CIEC), University of Minho, 4710-057 Braga, Portugal
| | - Ivan Miguel Pires
- Escola de Ciências e Tecnologia, University of Trás-os-Montes e Alto Douro, Quinta de Prados, 5001-801 Vila Real, Portugal;
- Instituto de Telecomunicações, Universidade da Beira Interior, 6200-001 Covilhã, Portugal;
- Correspondence: ; Tel.: +351-966-379-785
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Abstract
At present, diverse, innovative technology is used in electronics and ubiquitous computing environments [...]
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Abstract
The wide-spread use of wearables and the adoption of the Internet of Things (IoT) paradigm provide an opportunity to use mobile-device sensors for medical applications. Sensors available in the commonly used devices may inspire innovative solutions for physiotherapy striving for accurate and early identification of various pathologies. An essential and reliable performance measure is the ten-meter walk test, which is employed to determine functional mobility, gait, and vestibular function. Sensor-based approaches can identify the various test phases and their segmented duration, among other parameters. The measurement parameter primarily used is related to the tests’ duration, and after identifying patterns, a variety of physical treatments can be recommended. This paper reviews multiple studies focusing on automated measurements of the ten-meter walk test with different sensors. Most of the analyzed studies measure similar parameters as traditional methods, such as velocity, duration, and other involuntary and dangerous patients’ movements after stroke. That provides an opportunity to measure different parameters that can be later fed into machine learning models for analyzing more complex patterns.
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