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Willingham TB, Stowell J, Collier G, Backus D. Leveraging Emerging Technologies to Expand Accessibility and Improve Precision in Rehabilitation and Exercise for People with Disabilities. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2024; 21:79. [PMID: 38248542 PMCID: PMC10815484 DOI: 10.3390/ijerph21010079] [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: 11/13/2023] [Revised: 12/20/2023] [Accepted: 12/28/2023] [Indexed: 01/23/2024]
Abstract
Physical rehabilitation and exercise training have emerged as promising solutions for improving health, restoring function, and preserving quality of life in populations that face disparate health challenges related to disability. Despite the immense potential for rehabilitation and exercise to help people with disabilities live longer, healthier, and more independent lives, people with disabilities can experience physical, psychosocial, environmental, and economic barriers that limit their ability to participate in rehabilitation, exercise, and other physical activities. Together, these barriers contribute to health inequities in people with disabilities, by disproportionately limiting their ability to participate in health-promoting physical activities, relative to people without disabilities. Therefore, there is great need for research and innovation focusing on the development of strategies to expand accessibility and promote participation in rehabilitation and exercise programs for people with disabilities. Here, we discuss how cutting-edge technologies related to telecommunications, wearables, virtual and augmented reality, artificial intelligence, and cloud computing are providing new opportunities to improve accessibility in rehabilitation and exercise for people with disabilities. In addition, we highlight new frontiers in digital health technology and emerging lines of scientific research that will shape the future of precision care strategies for people with disabilities.
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Affiliation(s)
- T. Bradley Willingham
- Shepherd Center, Virginia C. Crawford Research Institute, Atlanta, GA 30309, USA (D.B.)
- Department of Physical Therapy, Georgia State University, Atlanta, GA 30302, USA
| | - Julie Stowell
- Shepherd Center, Virginia C. Crawford Research Institute, Atlanta, GA 30309, USA (D.B.)
- Department of Physical Therapy, Georgia State University, Atlanta, GA 30302, USA
| | - George Collier
- Shepherd Center, Virginia C. Crawford Research Institute, Atlanta, GA 30309, USA (D.B.)
| | - Deborah Backus
- Shepherd Center, Virginia C. Crawford Research Institute, Atlanta, GA 30309, USA (D.B.)
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Uwamahoro R, Sundaraj K, Subramaniam ID. Assessment of muscle activity using electrical stimulation and mechanomyography: a systematic review. Biomed Eng Online 2021; 20:1. [PMID: 33390158 PMCID: PMC7780389 DOI: 10.1186/s12938-020-00840-w] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 12/11/2020] [Indexed: 11/10/2022] Open
Abstract
This research has proved that mechanomyographic (MMG) signals can be used for evaluating muscle performance. Stimulation of the lost physiological functions of a muscle using an electrical signal has been determined crucial in clinical and experimental settings in which voluntary contraction fails in stimulating specific muscles. Previous studies have already indicated that characterizing contractile properties of muscles using MMG through neuromuscular electrical stimulation (NMES) showed excellent reliability. Thus, this review highlights the use of MMG signals on evaluating skeletal muscles under electrical stimulation. In total, 336 original articles were identified from the Scopus and SpringerLink electronic databases using search keywords for studies published between 2000 and 2020, and their eligibility for inclusion in this review has been screened using various inclusion criteria. After screening, 62 studies remained for analysis, with two additional articles from the bibliography, were categorized into the following: (1) fatigue, (2) torque, (3) force, (4) stiffness, (5) electrode development, (6) reliability of MMG and NMES approaches, and (7) validation of these techniques in clinical monitoring. This review has found that MMG through NMES provides feature factors for muscle activity assessment, highlighting standardized electromyostimulation and MMG parameters from different experimental protocols. Despite the evidence of mathematical computations in quantifying MMG along with NMES, the requirement of the processing speed, and fluctuation of MMG signals influence the technique to be prone to errors. Interestingly, although this review does not focus on machine learning, there are only few studies that have adopted it as an alternative to statistical analysis in the assessment of muscle fatigue, torque, and force. The results confirm the need for further investigation on the use of sophisticated computations of features of MMG signals from electrically stimulated muscles in muscle function assessment and assistive technology such as prosthetics control.
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Affiliation(s)
- Raphael Uwamahoro
- Fakulti Kejuruteraan Elektronik & Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Tunggal, Malaysia
- Regional Centre of Excellence in Biomedical Engineering and E-Health, University of Rwanda, PO BOX 4285, Kigali, Rwanda
| | - Kenneth Sundaraj
- Fakulti Kejuruteraan Elektronik & Kejuruteraan Komputer, Universiti Teknikal Malaysia Melaka, Tunggal, Malaysia.
| | - Indra Devi Subramaniam
- Pusat Bahasa & Pembangunan Insan, Universiti Teknikal Malaysia Melaka, Tunggal, Malaysia
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Devasahayam AJ, Chaves AR, Lasisi WO, Curtis ME, Wadden KP, Kelly LP, Pretty R, Chen A, Wallack EM, Newell CJ, Williams JB, Kenny H, Downer MB, McCarthy J, Moore CS, Ploughman M. Vigorous cool room treadmill training to improve walking ability in people with multiple sclerosis who use ambulatory assistive devices: a feasibility study. BMC Neurol 2020; 20:33. [PMID: 31969132 PMCID: PMC6975092 DOI: 10.1186/s12883-020-1611-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 01/10/2020] [Indexed: 02/08/2023] Open
Abstract
Background Aerobic training has the potential to restore function, stimulate brain repair, and reduce inflammation in people with Multiple Sclerosis (MS). However, disability, fatigue, and heat sensitivity are major barriers to exercise for people with MS. We aimed to determine the feasibility of conducting vigorous harness-supported treadmill training in a room cooled to 16 °C (10 weeks; 3times/week) and examine the longer-term effects on markers of function, brain repair, and inflammation among those using ambulatory aids. Methods Ten participants (9 females) aged 29 to 74 years with an Expanded Disability Status Scale ranging from 6 to 7 underwent training (40 to 65% heart rate reserve) starting at 80% self-selected walking speed. Feasibility of conducting vigorous training was assessed using a checklist, which included attendance rates, number of missed appointments, reasons for not attending, adverse events, safety hazards during training, reasons for dropout, tolerance to training load, subjective reporting of symptom worsening during and after exercise, and physiological responses to exercise. Functional outcomes were assessed before, after, and 3 months after training. Walking ability was measured using Timed 25 Foot Walk test and on an instrumented walkway at both fast and self-selected speeds. Fatigue was measured using fatigue/energy/vitality sub-scale of 36-Item Short-Form (SF-36) Health Survey, Fatigue Severity Scale, modified Fatigue Impact Scale. Aerobic fitness (maximal oxygen consumption) was measured using maximal graded exercise test (GXT). Quality-of-life was measured using SF-36 Health Survey. Serum levels of neurotrophin (brain-derived neurotrophic factor) and cytokine (interleukin-6) were assessed before and after GXT. Results Eight of the ten participants completed training (attendance rates ≥ 80%). No adverse events were observed. Fast walking speed (cm/s), gait quality (double-support (%)) while walking at self-selected speed, fatigue (modified Fatigue Impact Scale), fitness (maximal workload achieved during GXT), and quality-of-life (physical functioning sub-scale of SF-36) improved significantly after training, and improvements were sustained after 3-months. Improvements in fitness (maximal respiratory exchange ratio and maximal oxygen consumption during GXT) were associated with increased brain-derived neurotrophic factor and decreased interleukin-6. Conclusion Vigorous cool room training is feasible and can potentially improve walking, fatigue, fitness, and quality-of-life among people with moderate to severe MS-related disability. Trial registration The study was approved by the Newfoundland and Labrador Health Research Ethics Board (reference number: 2018.088) on 11/07/2018 prior to the enrollment of first participant (retrospectively registered at ClinicalTrials.gov: NCT04066972. Registered on 26 August 2019.
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Affiliation(s)
- Augustine J Devasahayam
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Arthur R Chaves
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Wendy O Lasisi
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Marie E Curtis
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Katie P Wadden
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Liam P Kelly
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Ryan Pretty
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Alice Chen
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Elizabeth M Wallack
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Caitlin J Newell
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - John B Williams
- Division of BioMedical Sciences, Faculty of Medicine, Memorial University of Newfoundland, Rm H4360, 300 Prince Philip Drive, St. John's, NL, A1B 3V6, Canada
| | - Hannah Kenny
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Matthew B Downer
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Jason McCarthy
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada
| | - Craig S Moore
- Division of BioMedical Sciences, Faculty of Medicine, Memorial University of Newfoundland, Rm H4360, 300 Prince Philip Drive, St. John's, NL, A1B 3V6, Canada
| | - Michelle Ploughman
- Recovery & Performance Laboratory, Faculty of Medicine, Memorial University of Newfoundland, Rm 400, L.A. Miller Centre, 100 Forest Road, St. John's, NL, A1A 1E5, Canada.
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Luo L, Zhu S, Shi L, Wang P, Li M, Yuan S. High Intensity Exercise for Walking Competency in Individuals with Stroke: A Systematic Review and Meta-Analysis. J Stroke Cerebrovasc Dis 2019; 28:104414. [PMID: 31570262 DOI: 10.1016/j.jstrokecerebrovasdis.2019.104414] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 08/28/2019] [Accepted: 09/10/2019] [Indexed: 10/25/2022] Open
Abstract
OBJECTIVE To assess the effects of high intensity exercise on walking competency in individuals with stroke. DATA SOURCES A systematic electronic searching of the PubMed, EMBASE, Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), CINAHL (EBSCOhost), and SPORTSDiscus (EBSCOhost) was initially performed up to June 25, 2019. STUDY SELECTION Randomized controlled trials or clinical controlled trials comparing any walking or gait parameters of the high intensity exercise to lower intensity exercise or usual physical activities were included. The risk of bias of included studies was assessed by the Cochrane risk of bias tool. The quality of evidence was assessed using GRADE (Grading of Recommendations, Assessment, Development and Evaluation) system. DATA EXTRACTION Data were extracted by 2 independent coders. The mean and standard deviation of the baseline and endpoint scores after training for walking distance, comfortable gait speed, gait analysis (cadence, stride length, and the gait symmetry), cost of walking, Berg Balance Scale , Time Up&Go (TUG) Test and adverse events were extracted. DATA SYNTHESIS A total of 22 (n = 952) studies were included. Standardized mean difference (SMD), weighted mean difference (WMD), and odds ratios (ORs) were used to compute effect size and subgroup analysis was conducted to test the consistency of results with different characteristics of exercise and time since stroke. Sensitivity analysis was used to assess the robustness of the results, which revealed significant differences on walking distance (SMD = .32, 95% CI, .17-.46, P < .01, I2 = 39%; WMD = 21.76 m), comfortable gait speed (SMD = .28, 95% CI, .06-.49, P = .01, I2 = 47%; WMD = .04 m/s), stride length (SMD = .51, 95% CI, .13-.88, P < .01, I2 = 0%; WMD = .12 m) and TUG (SMD = -.36, 95% CI, -.72 to .01, P = .05, I2 = 9%; WMD = -1.89 s) in favor of high intensity exercise versus control group. No significant differences were found between the high intensity exercise and control group in adverse events, including falls (OR = 1.40, 95% CI, .69-2.85, P = .35, I2 = 11%), pain (OR = 3.34, 95% CI, .82-13.51, P = .09, I2 = 0%), and skin injuries (OR = 1.08, 95% CI, .30-3.90, P = .90, I2 = 0%). CONCLUSIONS This systematic review suggests that high intensity exercise could be safe and more potent stimulus in enhancing walking competency in stroke survivors, with a capacity to improve walking distance, comfortable gait speed, stride length, and TUG compared with low to moderate intensity exercise or usual physical activities.
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Affiliation(s)
- Lu Luo
- Department of Rehabilitation Medicine, Fudan University, Shanghai, China
| | - Shiqiang Zhu
- Department of Rehabilitation Medicine, Ningxia Medical University, Ningxia, China
| | - Luoyi Shi
- Department of Rehabilitation Medicine, Taihe Hospital, Shiyan, China
| | - Peng Wang
- Department of Rehabilitation Medicine, Taihe Hospital, Shiyan, China
| | - Mengying Li
- Department of Rehabilitation Medicine, Taihe Hospital, Shiyan, China
| | - Song Yuan
- Department of Rehabilitation Medicine, Taihe Hospital, Shiyan, China.
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McCully KK, Moraes C, Patel SV, Green M, Willingham TB. Muscle-Specific Endurance of the Lower Back Erectors Using Electrical Twitch Mechanomyography. J Funct Morphol Kinesiol 2019; 4:jfmk4010012. [PMID: 33467327 PMCID: PMC7739340 DOI: 10.3390/jfmk4010012] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 01/22/2019] [Accepted: 01/23/2019] [Indexed: 11/30/2022] Open
Abstract
Lower back pain is a common symptom potentially associated with skeletal muscle dysfunction. The purpose of this study was to evaluate endurance in the lower back muscles of healthy participants using accelerometer-based mechanomyography. Methods: Young healthy subjects (N = 7) were tested. Surface electrodes and a tri-axial accelerometer were placed over the erector spinae muscle along the T11-L1 Vertebrae. Stimulation was for 3 min each at 2, 4, and 6 Hz, and changes in acceleration were used to calculate an endurance index (EI). Reproducibility of the endurance index measurements was tested on two separate days. Wrist flexor and vastus lateralis muscles were tested for comparison. Near Infrared Spectroscopy (NIRS) was used to measure muscle oxygen levels (O2Hb) (N = 5). EI was 70.3 + 13.4, 32.6 + 8.4, and 19.2 + 6.2% for 2, 4, 6 Hz, respectively. The coefficients of variation were 9.8, 13.9, and 20.3% for 2, 4, 6 Hz, respectively. EI values were lower in the erector spinae muscles compared to the arm and the leg (p < 0.05). O2Hb values were 86.4 + 10.9% at rest and were 77.2 + 15.5, 84.3 + 14.1, and 84.1 + 18.9% for 2, 4, 6 Hz, respectively (p > 0.05, all comparisons). An endurance index can be obtained from the lower back erectors muscles that is reproducible and not influenced by voluntary effort or muscle oxygen levels.
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Affiliation(s)
- Kevin K. McCully
- Department of Kinesiology, University of Georgia, Athens, GA 30602, USA
- Correspondence: ; Tel.: +1-706-542-1129
| | - Caio Moraes
- Department of Kinesiology, University of Georgia, Athens, GA 30602, USA
| | - Sahil V. Patel
- Department of Kinesiology, University of Georgia, Athens, GA 30602, USA
| | - Max Green
- AU-UGA Medical Partnership, Athens, GA 30606, USA
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