A Novel Wearable Foot and Ankle Monitoring System for the Assessment of Gait Biomechanics

Faragó, Paul; Grama, Lacrimioara; Hintea, Sorin

doi:10.3390/app11010268

Cited by 15 publications

(19 citation statements)

References 43 publications

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“…In addition, the knee abduction angle and abductor moments were greater in yoga than in ADL [30]. Thus, this point should be kept in mind when considering yoga as a therapeutic or rehabilitation approach for knee joint disorders [35,36].…”

Section: Lower Limb Joint Anglementioning

confidence: 98%

“…The finding is particularly interesting for elderly people who utilise the hip strategy during gait rather than ankle strategies [28]. Therefore, practising yoga should be recommended to the elderly to maintain postural stability [26], to those with the high possibility of fall [40], and to those with diabetes and peripheral neuropathy who suffer from impaired sensation in the ankles and feet [36,41].…”

Section: 3mentioning

confidence: 99%

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Biomechanical Characteristics on the Lower Extremity of Three Typical Yoga Manoeuvres

Whissell

Wang

et al. 2021

Applied Bionics and Biomechanics

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This study was aimed at exploring the biomechanical characteristics of the lower extremity amongst three typical yoga manoeuvres. A total of thirteen experienced female yoga practitioners were recruited in the current study; they were all certified with the Yoga Alliance. A three-dimensional motion capture system with 10 cameras combined with four synchronised force plates was used to collect kinematics of the lower extremity and ground reactive force whilst the participants performed the crescent lunge pose, warrior II pose, and triangle pose. One-way repeated ANOVA was used in exploring the differences amongst the three yoga movements, and the significance was set to alpha < 0.05 . The triangle pose performed the largest range of motion (ROM) of the hip ( 90.5 ° ± 22.9 ° ), knee ( 68.8 ° ± 23.1 ° ), and ankle ( 46.4 ° ± 11.3 ° ) in the sagittal plane and the hip ( 54.8 ° ± 6.5 ° ), knee ( 42.4 ° ± 12.8 ° ), and ankle ( 4.8 ° ± 1.7 ° ) in the frontal plane amongst the three manoeuvres ( P < 0.05 ). No significant difference was found for the hip and ankle joint moment amongst the three manoeuvres ( P > 0.05 ). Knee joint travelled into 9.5° of extension and slight adduction of 1.94° whilst expressing the largest knee joint adduction moments ( 0.30 ± 0.22 Nm / kg ) in the triangle pose. The distribution of the angular impulse of the lower limb joints indicated that the hip joint contributed significantly the most in the sagittal and frontal planes of the three yoga manoeuvres ( P < 0.05 ), ranging from 51.67% to 70.56%. Results indicated that triangle pose may be superior to the other two manoeuvres, which improved hip joint ROM, strength, and dynamic stability. However, knee injuries such as osteoarthritis (OA) should be considered because of the large knee extensor angle and adductor moments.

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Section: Lower Limb Joint Anglementioning

confidence: 98%

Section: 3mentioning

confidence: 99%

Biomechanical Characteristics on the Lower Extremity of Three Typical Yoga Manoeuvres

Whissell

Wang

et al. 2021

Applied Bionics and Biomechanics

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“…The use of wearable technologies can be perfectly adapted to assist in motor rehabilitation interventions (Ianculescu et al, 2019;Bonato et al, 2003) both of upper limbs where Cifuentes (Cifuentes et al, 2012) uses wearable devices to assist in the rehabilitation of individuals after stroke, as well as in the rehabilitation of lower limbs where electromyography sensors (EMG), inertial measurement unit (IMUs) and pressure sensors can assist in the evaluation and rehabilitation of knee osteoarthritis (Chen et al, 2017) and the evaluation of gait biomechanics (Faragó et al,2021;Gouwanda et al, 2016).…”

Section: Smart Wearable Devicesmentioning

confidence: 99%

Development and Test of a Serious Game for Dorsiflexion and Plantarflexion Exercises of the Feet

Ferreira

Baptista

Rodrigues

et al. 2021

JIS

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Congenital clubfoot is the most common disease of the musculoskeletal system, causing deformities in the musculature of the foot and requiring long-term motor rehabilitation. This article shows the design and development of a serious game to support the process of motor rehabilitation of clubfoot through dorsiflexion and plantarflexion exercises. The game is controlled by a wearable device (Papeteshoes), where the accelerometers are responsible for detecting the movement of the foot. A pilot test was carried out withtwo children with and without clubfoot (Congenital Talipes Equi-novarus-CTE) to examine the feasibility of the game as a therapy instrument. Usability and applicability questionnaires were applied after using the game. The results show that both children reacted in the same way to the proposals, performing the necessary movements for the motor recruitment of the muscles related to the leg and foot and maintaining the range of motion of the ankle joint.

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“…Chen et al [ 8 ] proposed a gait classification and develop a simple and efficient method for the quantification method for parkinsonian gait from monocular video imaging based on kernel-based principal component analysis. Faragó et al [ 9 , 10 ] proposed a framework for classifying normal walking, heel-walking, and toe-walking based on the cross-correlation of plantar pressures with corresponding lower-limb EMG signals.…”

Section: Introductionmentioning

confidence: 99%

Machine-learning-based children’s pathological gait classification with low-cost gait-recognition system

Chen

Wang

et al. 2021

BioMed Eng OnLine

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Background Pathological gaits of children may lead to terrible diseases, such as osteoarthritis or scoliosis. By monitoring the gait pattern of a child, proper therapeutic measures can be recommended to avoid the terrible consequence. However, low-cost systems for pathological gait recognition of children automatically have not been on market yet. Our goal was to design a low-cost gait-recognition system for children with only pressure information. Methods In this study, we design a pathological gait-recognition system (PGRS) with an 8 × 8 pressure-sensor array. An intelligent gait-recognition method (IGRM) based on machine learning and pure plantar pressure information is also proposed in static and dynamic sections to realize high accuracy and good real-time performance. To verifying the recognition effect, a total of 17 children were recruited in the experiments wearing PGRS to recognize three pathological gaits (toe-in, toe-out, and flat) and normal gait. Children are asked to walk naturally on level ground in the dynamic section or stand naturally and comfortably in the static section. The evaluation of the performance of recognition results included stratified tenfold cross-validation with recall, precision, and a time cost as metrics. Results The experimental results show that all of the IGRMs have been identified with a practically applicable degree of average accuracy either in the dynamic or static section. Experimental results indicate that the IGRM has 92.41% and 97.79% intra-subject recognition accuracy, and 85.78% and 78.81% inter-subject recognition accuracy, respectively, in the static and dynamic sections. And we find methods in the static section have less recognition accuracy due to the unnatural gesture of children when standing. Conclusions In this study, a low-cost PGRS has been verified and realize feasibility, highly average precision, and good real-time performance of gait recognition. The experimental results reveal the potential for the computer supervision of non-pathological and pathological gaits in the plantar-pressure patterns of children and for providing feedback in the application of gait-abnormality rectification.

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A Novel Wearable Foot and Ankle Monitoring System for the Assessment of Gait Biomechanics

Cited by 15 publications

References 43 publications

Biomechanical Characteristics on the Lower Extremity of Three Typical Yoga Manoeuvres

Biomechanical Characteristics on the Lower Extremity of Three Typical Yoga Manoeuvres

Development and Test of a Serious Game for Dorsiflexion and Plantarflexion Exercises of the Feet

Machine-learning-based children’s pathological gait classification with low-cost gait-recognition system

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