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Terao Y, Hosaka N, Otobe Y, Suzuki M, Kojima I, Yoshizawa K, Yamada M, Nakayama Y, Abo M. The impact of preoperative muscle strength on postoperative walking ability in patients undergoing total knee arthroplasty. Int J Rehabil Res 2023; 46:157-162. [PMID: 36867015 DOI: 10.1097/mrr.0000000000000572] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
Although knee extensor muscle strength is strongly associated with postoperative walking ability (PWA) in patients undergoing total knee arthroplasty (TKA), few studies have considered the impact of both knee extensor and flexor muscle strength. This study aimed to determine whether operative side knee flexor and extensor muscle strength before surgery affects the PWA of patients who undergo TKA while accounting for potential covariates. This multicenter retrospective cohort study involved four university hospitals, and patients who underwent unilateral primary TKA were included. The outcome measure was the 5-m maximum walking speed test (MWS), which was completed 12 weeks postoperatively. Muscle strength was measured as the maximum isometric muscle strength required for knee flexor and extensor. Three multiple regression models with a progressively larger number of variables were developed to determine the predictors of 5-m MWS at 12 weeks post-TKA surgery. One hundred thirty-one patients who underwent TKA were enrolled in the study (men, 23.7%; mean age, 73.4 ± 6.9 years). Age, sex, operative side knee flexor muscle strength before surgery, Japanese Orthopaedic Association knee score, and preoperative walking ability were significantly associated with PWA in the final model of the multiple regression analysis ( R2 = 0.35). The current findings suggest that the operative side knee flexor muscle strength before surgery is a robust modifiable predictor of improved PWA. We believe that further validation is needed to determine the causal relationship between preoperative muscle strength and PWA.
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Affiliation(s)
- Yusuke Terao
- Department of Rehabilitation Medicine, The Jikei University School of Medicine Hospital
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tokyo
| | - Naoki Hosaka
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tokyo
| | - Yuhei Otobe
- Department of Rehabilitation Science, Physical Therapy Course, School of Medicine, Osaka Metropolitan University, Osaka
| | - Mizue Suzuki
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tokyo
| | - Iwao Kojima
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tokyo
| | - Kazuya Yoshizawa
- Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tokyo
| | | | - Yasuhide Nakayama
- Department of Rehabilitation Medicine, The Jikei University School of Medicine Hospital
| | - Masahiro Abo
- Department of Rehabilitation Medicine, The Jikei University School of Medicine, Tokyo, Japan
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Kokkotis C, Chalatsis G, Moustakidis S, Siouras A, Mitrousias V, Tsaopoulos D, Patikas D, Aggelousis N, Hantes M, Giakas G, Katsavelis D, Tsatalas T. Identifying Gait-Related Functional Outcomes in Post-Knee Surgery Patients Using Machine Learning: A Systematic Review. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 20:448. [PMID: 36612771 PMCID: PMC9819733 DOI: 10.3390/ijerph20010448] [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: 11/30/2022] [Revised: 12/24/2022] [Accepted: 12/26/2022] [Indexed: 06/17/2023]
Abstract
Modern lifestyles require new tools for determining a person's ability to return to daily activities after knee surgery. These quantitative instruments must feature high discrimination, be non-invasive, and be inexpensive. Machine learning is a revolutionary approach that has the potential to satisfy the aforementioned requirements and bridge the knowledge gap. The scope of this study is to summarize the results of a systematic literature review on the identification of gait-related changes and the determination of the functional recovery status of patients after knee surgery using advanced machine learning algorithms. The current systematic review was conducted using multiple databases in accordance with the PRISMA guidelines, including Scopus, PubMed, and Semantic Scholar. Six out of the 405 articles met our inclusion criteria and were directly related to the quantification of the recovery status using machine learning and gait data. The results were interpreted using appropriate metrics. The results demonstrated a recent increase in the use of sophisticated machine learning techniques that can provide robust decision-making support during personalized post-treatment interventions for knee-surgery patients.
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Affiliation(s)
- Christos Kokkotis
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece
| | - Georgios Chalatsis
- Department of Orthopedic Surgery, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece
| | | | - Athanasios Siouras
- AIDEAS OÜ, 10117 Tallinn, Estonia
- Department of Computer Science and Biomedical Informatics, School of Science, University of Thessaly, 35131 Lamia, Greece
| | - Vasileios Mitrousias
- Department of Orthopedic Surgery, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece
| | - Dimitrios Tsaopoulos
- Institute for Bio-Economy and Agri-Technology, Center for Research and Technology Hellas, 38333 Volos, Greece
| | - Dimitrios Patikas
- School of Physical Education and Sports Science at Serres, Aristotle University of Thessaloniki, 62110 Serres, Greece
| | - Nikolaos Aggelousis
- Department of Physical Education and Sport Science, Democritus University of Thrace, 69100 Komotini, Greece
| | - Michael Hantes
- Department of Orthopedic Surgery, Faculty of Medicine, University of Thessaly, 41500 Larissa, Greece
| | - Giannis Giakas
- Department of Physical Education and Sport Science, University of Thessaly, 42100 Trikala, Greece
| | - Dimitrios Katsavelis
- Department of Exercise Science and Pre-Health Profession, Creighton University, Omaha, NE 68178, USA
| | - Themistoklis Tsatalas
- Department of Physical Education and Sport Science, University of Thessaly, 42100 Trikala, Greece
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Çetinkaya F, Karakoyun A. The effects of elastic band exercise on the pain, kinesiophobia, functional, and psychological status after total knee arthroplasty: a randomized controlled trial. Clin Rheumatol 2022; 41:3179-3188. [PMID: 35776283 DOI: 10.1007/s10067-022-06266-0] [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: 05/20/2022] [Revised: 06/21/2022] [Accepted: 06/24/2022] [Indexed: 11/03/2022]
Abstract
INTRODUCTION Elastic band exercise not only improves muscle strength and elasticity, increases efficiency, balance, and quality of life but also decreases the injury risk. This study was conducted to determine the effect of elastic band exercise on pain, kinesiophobia, functional, and psychological status after total knee arthroplasty. METHODS This study was conducted out between October 2019 and April 2020 as a randomized controlled experimental study with a total of 60 patients. Data collection tools in this study included a descriptive information form, visual analog scale, Tampa Kinesiophobia, WOMAC Osteoarthritis Index, and Beck Depression Inventory. RESULTS Before intervention, the total score of VAS, WOMAC, Tampa Kinesiophobia, and Beck Depression showed no statistically significant difference between intervention group and control group. However, 4 weeks after intervention observed a statistically significant difference between the intervention and control groups in terms of VAS (U = 10,000; p < 0.001), WOMAC (U = 0.00; p < 0.001), Tampa Kinesiophobia (U = 221.5; p = 0.001), and Beck Depression means score (U = 112.5; p < 0.001). In addition, 4 weeks after the intervention, joint range and walking test assessments were statistically significant between the intervention and control groups (p < 0.001). CONCLUSION The results of the research showed that elastic band exercise had a positive effect on psychological and functional capacity. TRIAL REGISTRATION This study is registered in the Clinical Trial Registry (registration number NCT04981106) Key points • Patients with total knee arthroplasty require rehabilitation exercise to avoid physical function weakness. • Elastic band exercise significantly reduces patients' fear of movement and depression. • Elastic band exercise activities facilitate significant physical motion function. • Elastic band exercise inspires the will of patients to engage in home rehabilitation exercise patients after total knee arthroplasty.
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Affiliation(s)
- Funda Çetinkaya
- Department of Surgical Nursing, Faculty of Health Sciences, Aksaray University, Aksaray, Turkey.
| | - Ahmet Karakoyun
- Department Physical Therapy And Rehabilitation, Faculty of Medicine, Aksaray University, Aksaray, Turkey
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Zandiyeh P, Parola LR, Fleming BC, Beveridge JE. Wavelet analysis reveals differential lower limb muscle activity patterns long after anterior cruciate ligament reconstruction. J Biomech 2022; 133:110957. [PMID: 35114581 PMCID: PMC8893161 DOI: 10.1016/j.jbiomech.2022.110957] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 01/05/2022] [Accepted: 01/06/2022] [Indexed: 10/19/2022]
Abstract
The purpose of this study was to test whether differences in muscle activity patterns between anterior cruciate ligament-reconstructed patients (ACLR) and healthy controls could be detected 10 to 15 years post-surgery using a machine learning classification approach. Eleven ACLR subjects and 12 healthy controls were recruited from an ongoing prospective randomized clinical trial. Surface electromyography (EMG) signals were recorded from gastrocnemius medialis and lateralis, tibialis anterior, vastus medialis, rectus femoris, biceps femoris, and semitendinosus muscles. Muscle activity was analyzed using wavelet analysis and examined within four sub-phases of the hop test, as well as an average of the task as a whole. K-nearest neighbor machine learning combined with a leave-one-out validation was used to classify the muscle activity patterns as either ACLR or Control. When muscle activity was averaged across the whole hop task, activity patterns for all muscles except the tibialis anterior were identified as being different between the study cohorts. ACLR patients demonstrated continuous muscle activities that spanned take-off, airborne, and landing hop phases versus healthy controls who displayed timed and regulated islets of muscle activities specific to each hop phase. The most striking features were 25-50% greater relative quadriceps intensity and approximately 66% diminished biceps femoris intensity in ACLR patients. The current findings are in contrast to previous work using conventional co-contraction and muscle activation onset EMG measures of the same dataset, underscoring the sensitivity and potential of the wavelet approach coupled with machine learning to reveal meaningful adaptation strategies in this at-risk population.
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Affiliation(s)
- Payam Zandiyeh
- Department of Orthopaedic Surgery, University of Texas Health Sciences Center at Houston, TX, USA.
| | - Lauren R. Parola
- Department of Orthopaedics, Warren Alpert Medical School of Brown University/Rhode Island Hospital, Providence, RI, USA
| | - Braden C. Fleming
- Department of Orthopaedics, Warren Alpert Medical School of Brown University/Rhode Island Hospital, Providence, RI, USA
| | - Jillian E. Beveridge
- Department of Orthopaedics, Warren Alpert Medical School of Brown University/Rhode Island Hospital, Providence, RI, USA.,Cleveland Clinic Biomedical Engineering Department, Cleveland, OH, USA.,Corresponding Author: Dr. Jillian Beveridge, Cleveland Clinic Biomedical Engineering Department, 9500 Euclid Avenue/ND20, Cleveland, OH, 44195, USA; ; P: (216) 299-3993
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Kim H, Palmieri-Smith R, Kipp K. Time-frequency analysis of muscle activation patterns in people with chronic ankle instability during Landing and cutting tasks. Gait Posture 2020; 82:203-208. [PMID: 32949904 DOI: 10.1016/j.gaitpost.2020.09.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 08/03/2020] [Accepted: 09/03/2020] [Indexed: 02/02/2023]
Abstract
BACKGROUND People with chronic ankle instability (CAI) exhibit neuromuscular deficits. Previous studies, however, only investigated magnitudes of muscle activation and not the time-frequency domain. RESEARCH QUESTION Do people with CAI exhibit differences in muscle activation patterns in the time-frequency domain during landing, anticipated cutting, and unanticipated cutting compared to matched controls? METHODS Eleven people with CAI and eleven healthy matched controls (CON) performed landing, anticipated cutting, and unanticipated cutting as surface EMG of the lateral gastrocnemius, medial gastrocnemius, fibularis longus, soleus, and tibialis anterior were recorded. The time-frequency domain of surface EMG data was analyzed with wavelet transformations and principal component analysis (PCA), PC scores were compared across group, task, and muscle with three-way ANOVAs. RESULTS The PCA extracted two PCs that captured the overall magnitude (PC1) of wavelet intensities across the time-frequency domain and a shift among the range of frequencies (PC2) where wavelet intensities were most prominent. A main effect for group indicated that people with CAI demonstrated smaller (p = 0.009) PC1 scores than people in the CON group across all muscles and tasks. An interaction between group and task indicated that people in the CAI group exhibited smaller (p = 0.041) PC2 scores than people in the CON group during only anticipated cutting. SIGNIFICANCE People with CAI exhibited neuromuscular deficits in the time-frequency domain of EMG during dynamic tasks. These deficits appear to reflect a neuromuscular strategy characterized by the recruitment of fewer motor units in ankle muscles regardless of task, and an inability to scale the recruitment of motor units in the frequency domain in response to different task demands. Rehabilitation for people with CAI should consider that this population exhibits differences in neuromuscular control that exist not only in the overall magnitudes, but also in the time-frequency domain, of muscle activation patterns.
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Affiliation(s)
- Hoon Kim
- Department of Physical Therapy - Program in Exercise & Rehabilitation Science, Marquette University, Cramer Hall 004B, 604 N. 16th St. 004B, Milwaukee, WI, 53233, USA.
| | - Riann Palmieri-Smith
- School of Kinesiology, University of Michigan, CCRB 4745G, 401 Washtenaw Ave., Ann Arbor, MI, 48109-2214, USA; Orthopaedic and Rehabilitation Biomechanics Laboratory, University of Michigan, CCRB 4745G, 401 Washtenaw Ave., Ann Arbor, MI, 48109-2214, USA.
| | - Kristof Kipp
- Department of Physical Therapy - Program in Exercise & Rehabilitation Science, Marquette University, Cramer Hall 215D, 604 N. 16th St. 215D, Milwaukee, WI, 53233, USA.
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Abstract
The classification and monitoring of individuals with early knee osteoarthritis (OA) are important considerations for the design and evaluation of therapeutic interventions and require the identification of appropriate outcome measures. Potential outcome domains to assess for early OA include patient-reported outcomes (such as pain, function and quality of life), features of clinical examination (such as joint line tenderness and crepitus), objective measures of physical function, levels of physical activity, features of imaging modalities (such as of magnetic resonance imaging) and biochemical markers in body fluid. Patient characteristics such as adiposity and biomechanics of the knee could also have relevance to the assessment of early OA. Importantly, research is needed to enable the selection of outcome measures that are feasible, reliable and validated in individuals at risk of knee OA or with early knee OA. In this Perspectives article, potential outcome measures for early symptomatic knee OA are discussed, including those measures that could be of use in clinical practice and/or the research setting.
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Effects of Elastic Band Exercise on Lower Limb Rehabilitation of Elderly Patients Undergoing Total Knee Arthroplasty. Rehabil Nurs 2019; 44:60-66. [PMID: 30601799 DOI: 10.1097/rnj.0000000000000109] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE The aim of the study was to investigate the effect of elastic band exercise activities on lower extremity rehabilitation in elderly patients subjected to an elastic band exercise intervention 2 and 4 weeks after total knee arthroplasty. DESIGN A quasiexperimental study was conducted. Participants were recruited from southern Taiwan who were over 65 years old and had a first unilateral total knee arthroplasty for osteoarthritis. METHODS The control and experimental groups comprised 25 patients each. The control group received conventional treatment after total knee arthroplasty; by contrast, the experimental group engaged in elastic band exercise activities demonstrated by instructors, in addition to receiving conventional treatment. Effects of the lower extremity rehabilitation of the two groups were evaluated 2 and 4 weeks after total knee arthroplasty. FINDINGS Most of the participants were above 70 years of age, 17 of whom were in the control group (68%) and 16 in the experimental group (64%). The active and passive knee flexion angles of the experimental group were greater than those of the control group (p < .001) 2 and 4 weeks after surgery. The muscle strength of the quadriceps of the experimental group was higher than that of the control group (p < .001) 2 and 4 weeks after surgery. The experimental group exhibited significantly higher physical function than that of the control group 2 and 4 weeks after surgery (p < .001). CONCLUSIONS The elastic band exercise program shows promising effects on improving the lower limb rehabilitation of elderly patients with total knee arthroplasty. CLINICAL RELEVANCE Healthcare professionals who work with elderly patients with total knee arthroplasty may consider recommending and implementing the elastic band exercise program as a home rehabilitation method for this population. However, we recommend further testing of the long-term effects of this program on a larger population.
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von Tscharner V. A model computation of how synchronization and clustering of motor unit action potentials alter the power spectra of electromyograms. Biomed Signal Process Control 2019. [DOI: 10.1016/j.bspc.2018.09.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Koenig I, Eichelberger P, Blasimann A, Hauswirth A, Baeyens JP, Radlinger L. Wavelet analyses of electromyographic signals derived from lower extremity muscles while walking or running: A systematic review. PLoS One 2018; 13:e0206549. [PMID: 30388151 PMCID: PMC6214539 DOI: 10.1371/journal.pone.0206549] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2018] [Accepted: 10/15/2018] [Indexed: 11/30/2022] Open
Abstract
Surface electromyography is often used to assess muscle activity and muscle function. A wavelet approach provides information about the intensity of muscle activity and motor unit recruitment strategies at every time point of the gait cycle. The aim was to review papers that employed wavelet analyses to investigate electromyograms of lower extremity muscles during walking and running. Eleven databases were searched up until June 1st 2017. The composition was based on the PICO model and the PRISMA checklist. First author, year, subject characteristics, intervention, outcome measures & variables, results and wavelet specification were extracted. Eighteen studies included the use of wavelets to investigate electromyograms of lower extremity muscles. Three main topics were discussed: 1.) The capability of the method to correctly assign participants to a specific group (recognition rate) varied between 68.4%-100%. 2.) Patients with ankle osteoarthritis or total knee arthroplasty presented a delayed muscle activation in the early stance phase but a prolonged activation in mid stance. 3.) Atrophic muscles did not contain type II muscle fiber components but more energy in their lower frequencies. The simultaneous information of time, frequency and intensity is of high clinical relevance because it offers valuable information about pre-and reflex activation behavior on different walking and running speeds as well as spectral changes towards high or low frequencies at every time point of the gait cycle.
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Affiliation(s)
- Irene Koenig
- Bern University of Applied Sciences, Department of Health Professions, Division of Physiotherapy, Bern, Switzerland
- Vrije Universiteit Brussel, Faculty of Physical Education and Physiotherapy, Brussels, Belgium
- * E-mail:
| | - Patric Eichelberger
- Bern University of Applied Sciences, Department of Health Professions, Division of Physiotherapy, Bern, Switzerland
| | - Angela Blasimann
- Bern University of Applied Sciences, Department of Health Professions, Division of Physiotherapy, Bern, Switzerland
| | - Antonia Hauswirth
- Bern University of Applied Sciences, Department of Health Professions, Division of Physiotherapy, Bern, Switzerland
| | - Jean-Pierre Baeyens
- Bern University of Applied Sciences, Department of Health Professions, Division of Physiotherapy, Bern, Switzerland
- Vrije Universiteit Brussel, Faculty of Physical Education and Physiotherapy, Brussels, Belgium
| | - Lorenz Radlinger
- Bern University of Applied Sciences, Department of Health Professions, Division of Physiotherapy, Bern, Switzerland
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Halilaj E, Rajagopal A, Fiterau M, Hicks JL, Hastie TJ, Delp SL. Machine learning in human movement biomechanics: Best practices, common pitfalls, and new opportunities. J Biomech 2018; 81:1-11. [PMID: 30279002 DOI: 10.1016/j.jbiomech.2018.09.009] [Citation(s) in RCA: 187] [Impact Index Per Article: 31.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2018] [Accepted: 09/08/2018] [Indexed: 12/11/2022]
Abstract
Traditional laboratory experiments, rehabilitation clinics, and wearable sensors offer biomechanists a wealth of data on healthy and pathological movement. To harness the power of these data and make research more efficient, modern machine learning techniques are starting to complement traditional statistical tools. This survey summarizes the current usage of machine learning methods in human movement biomechanics and highlights best practices that will enable critical evaluation of the literature. We carried out a PubMed/Medline database search for original research articles that used machine learning to study movement biomechanics in patients with musculoskeletal and neuromuscular diseases. Most studies that met our inclusion criteria focused on classifying pathological movement, predicting risk of developing a disease, estimating the effect of an intervention, or automatically recognizing activities to facilitate out-of-clinic patient monitoring. We found that research studies build and evaluate models inconsistently, which motivated our discussion of best practices. We provide recommendations for training and evaluating machine learning models and discuss the potential of several underutilized approaches, such as deep learning, to generate new knowledge about human movement. We believe that cross-training biomechanists in data science and a cultural shift toward sharing of data and tools are essential to maximize the impact of biomechanics research.
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Affiliation(s)
- Eni Halilaj
- Department of Mechanical Engineering, Carnegie Mellon University, United States.
| | - Apoorva Rajagopal
- Department of Mechanical Engineering, Stanford University, United States
| | - Madalina Fiterau
- Department of Computer Science, Stanford University, United States
| | - Jennifer L Hicks
- Department of Bioengineering, Stanford University, United States
| | - Trevor J Hastie
- Department of Statistics, Stanford University, United States; Department of Health Research and Policy, Stanford University, United States
| | - Scott L Delp
- Department of Mechanical Engineering, Stanford University, United States; Department of Bioengineering, Stanford University, United States; Department of Orthopaedic Surgery, Stanford University, United States
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Kuntze G, von Tscharner V, Hutchison C, Ronsky JL. Alterations in lower limb multimuscle activation patterns during stair climbing in female total knee arthroplasty patients. J Neurophysiol 2015; 114:2718-25. [PMID: 26354313 DOI: 10.1152/jn.00370.2015] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2015] [Accepted: 09/04/2015] [Indexed: 11/22/2022] Open
Abstract
Total knee arthroplasty (TKA) patients commonly experience neuromuscular adaptations that may affect stair climbing competence. This study identified multimuscle pattern (MMP) changes in postoperative female TKA patients during stair climbing with a support vector machine (SVM). It was hypothesized that TKA patients adopt temporal and spectral muscle activation characteristics indicative of muscle atrophy and cocontraction strategies. Nineteen female subjects [10 unilateral sex-specific TKAs, 62.2 ± 8.6 yr, body mass index (BMI) 28.2 ± 5.4 kg/m(2); 9 healthy control subjects, 61.4 ± 7.4 yr, BMI 25.6 ± 2.4 kg/m(2)] were recruited. Surface electromyograms (EMGs) were obtained for seven lower limb muscles of the affected limb of TKA subjects and a randomly assigned limb for control subjects during stair climbing. Stance phase (±30%) EMG data were wavelet transformed and normalized to total power. Data across all muscles were combined to form MMPs and analyzed with a SVM. Statistical analysis was performed with binomial tests, independent group t-tests, or independent group Mann-Whitney U-tests in SPSS (P < 0.05). SVM results indicated significantly altered muscle activation patterns in the TKA group for biceps femoris (recognition rate 84.2%), semitendinosus (recognition rate 73.7%), gastrocnemius (recognition rate 68.4%), and tibialis anterior (recognition rate 68.4%). Further analysis identified no significant differences in spectral activation characteristics between groups. Temporal adaptations, indicative of cocontraction strategies, were, however, evident in TKA MMPs. This approach may provide a valuable tool for clinical neuromuscular function assessment and rehabilitation monitoring.
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Affiliation(s)
- G Kuntze
- Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada; Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada; and
| | - V von Tscharner
- Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada; and
| | - C Hutchison
- Cumming School of Medicine, University of Calgary, Calgary, Alberta, Canada
| | - J L Ronsky
- Schulich School of Engineering, University of Calgary, Calgary, Alberta, Canada
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