Dataset Information

Identification of Secondary Biomechanical Abnormalities in the Lower Limb Joints after Chronic Transtibial Amputation: A Proof-of-Concept Study Using SPM1D Analysis.

ABSTRACT: SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org). We present the potential application of MovementRx in the prediction of increased joint forces with the possibility to predispose to osteoarthritis in a sample of post-surgical Transtibial Amputation (TTA) patients who were ambulant in the community. We captured the three-dimensional movement profile of 12 males with TTA and studied them using MovementRx, employing the SPM1D Python library to quantify the deviation(s) they have from our corresponding reference data, using "Hotelling 2" and "T test 2" statistics for the 3D movement vectors of the 3 main lower limb joints (hip, knee, and ankle) and their nine respective components (3 joints × 3 dimensions), respectively. MovementRx results visually demonstrated a clear distinction in the biomechanical recordings between TTA patients and a reference set of normal people (ABILITY data project), and variability within the TTA patients' group enabled identification of those with an increased risk of developing osteoarthritis in the future. We conclude that MovementRx is a potential tool to detect increased specific joint forces with the ability to identify TTA survivors who may be at risk for osteoarthritis.

SUBMITTER: Alhossary A

PROVIDER: S-EPMC9311753 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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Publications

Identification of Secondary Biomechanical Abnormalities in the Lower Limb Joints after Chronic Transtibial Amputation: A Proof-of-Concept Study Using SPM1D Analysis.

Alhossary Amr A Ang Wei Tech WT Chua Karen Sui Geok KSG Tay Matthew Rong Jie MRJ Ong Poo Lee PL Murakami Tsurayuki T Quake Tabitha T Binedell Trevor T Wee Seng Kwee SK Phua Min Wee MW Wei Yong Jia YJ Donnelly Cyril John CJ

Bioengineering (Basel, Switzerland) 20220630 7

SPM is a statistical method of analysis of time-varying human movement gait signal, depending on the random field theory (RFT). MovementRx is our inhouse-developed decision-support system that depends on SPM1D Python implementation of the SPM (spm1d.org). We present the potential application of MovementRx in the prediction of increased joint forces with the possibility to predispose to osteoarthritis in a sample of post-surgical Transtibial Amputation (TTA) patients who were ambulant in the comm ...[more]

PMID: 35877344

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Project description:BackgroundPhysical activity (PA) is important to general health and knee osteoarthritis (OA). Excessive workplace PA is an established risk factor for knee OA however, appropriate methods of measurement are unclear. There is a need to examine and assess the utility of new methods of measuring workplace PA and estimating knee load prior to application to large-scale, knee OA cohorts. Our aims, therefore, were to monitor workplace PA and estimate lower-limb loading across different occupations in health participants.MethodsTwenty-four healthy adults, currently working full-time in a single occupation (≥ 35 h/week) and free of musculoskeletal disease, comorbidity and had no history of lower-limb injury/surgery (past 12-months) were recruited across New South Wales (Australia). A convenience sample was recruited with occupations assigned to levels of workload; sedentary, light manual and heavy manual. Metrics of workplace PA including tasks performed (i.e., sitting), step-count and lower-limb loading were monitored over 10 working days using a daily survey, smartwatch, and a smartphone.ResultsParticipants of light manual occupations had the greatest between-person variations in mean lower-limb load (from 2 to 59 kg*m/s3). Lower-limb load for most participants of the light manual group was similar to a single participant in heavy manual work (30 kg*m/s3) and was at least three times greater than the sedentary group (2 kg*m/s3). The trends of workplace PA over working hours were largely consistent, per individual, but rare events of extreme loads were observed across all participants (up to 760 kg*m/s3).ConclusionsThere are large interpersonal variations in metrics of workplace PA, particularly among light and heavy manual occupations. Our estimates of lower-limb loading were largely consistent with pre-conceived levels of physical demand. We present a new approach to monitoring PA and estimating lower-limb loading, which could be applied to future occupational studies of knee OA.

Project description:BackgroundTo evaluate cycling participation and identify barriers and facilitators related to cycling participation in people with a lower limb amputation (LLA) in the Netherlands.MethodsA questionnaire was sent to adults with a LLA between March and August 2019 to obtain information regarding prosthesis, individual's characteristics, amputation, cycling barriers and facilitators, and prosthetic satisfaction. The questionnaires were distributed via 8 orthopedic workshops, post and were given directly. To find cycling predictors, variables associated with cycling (p < 0.1) were entered into a logistic regression analysis. Non-significant variables were removed manually.ResultsParticipants (n = 207, 71% males) had a mean age of 62.0 ± 13.0 years. The most frequent level of amputation was transtibial (42%), and trauma was the most frequent cause of amputation (43%). After the LLA, 141 participants (68%) cycled for recreation (80%), physical fitness (74%), and transport (50%). In the past six months, cyclists cycled for recreation (79%) and transport (66%). Most cycled less than once a day. Recreational cyclists cycled alone (75%) for a median duration of 45 min or 14 km per ride. Cyclists with a transportation purpose usually cycled to go shopping (80%) or to visit friends (68%), with a median duration of 20 min or five kilometers per ride. Cyclists reported more facilitators (median (IQR) = 5 (3, 7) than non-cyclists 0 (0, 3). The majority of cyclists reported a positive attitude toward cycling (89%) and cycled because of health benefits (81%). A dynamic foot (odds ratio: 5.2, 95% CI 2.0, 13.3) and a higher number of facilitators (odds ratio: 1.3, 95% CI 1.2, 1.5) positively predicted cycling, whereas the presence of other underlying diseases (odds ratio: 0.4, 95% CI 0.2, 0.9) negatively predicted cycling (R2: 40.2%).ConclusionIn the Netherlands, the majority of adults cycled after a LLA, mainly for recreational purposes. A dynamic foot, a higher number of facilitators, and no other underlying diseases increases the likelihood of cycling after a LLA. The results suggest that personal motivation and a higher mobility level could be the key to increasing cycling participation. Future research should determine the association between motivation, mobility levels, and cycling with a LLA.

Dataset Information

Identification of Secondary Biomechanical Abnormalities in the Lower Limb Joints after Chronic Transtibial Amputation: A Proof-of-Concept Study Using SPM1D Analysis.

Publications

Identification of Secondary Biomechanical Abnormalities in the Lower Limb Joints after Chronic Transtibial Amputation: A Proof-of-Concept Study Using SPM1D Analysis.

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