Open source Vicon Toolkit for motion capture and Gait Analysis

Goldfarb, Nathaniel; Lewis, Alek; Tacescu, Alex; Fischer, Gregory S.

doi:10.1016/j.cmpb.2021.106414

Cited by 21 publications

(10 citation statements)

References 15 publications

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“…Our second objective was to differentiate individuals with sarcopenia from those with movement disorders by utilizing their physical functions. While numerous studies demonstrate the accuracy of tools like smart insoles and sensors in distinguishing between healthy individuals and patients, the significance of these findings can vary 33–35 . To address this, we introduced a classification model that incorporates the latest AI technique, pose estimation, along with a smart device, the insole.…”

Section: Discussionmentioning

confidence: 99%

“…While numerous studies demonstrate the accuracy of tools like smart insoles and sensors in distinguishing between healthy individuals and patients, the significance of these findings can vary. [33][34][35] To address this, we introduced a classification model that incorporates the latest AI technique, pose estimation, along with a smart device, the insole. Through the utilization of the aforementioned tools, we conducted an analysis using SVM, RF and ANN classification models.…”

Section: Discussionmentioning

confidence: 99%

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Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis

Kim,

Yoo

2023

J cachexia sarcopenia muscle

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BackgroundThe relationship between physical function, musculoskeletal disorders and sarcopenia is intricate. Current physical function tests, such as the gait speed test and the chair stand test, have limitations in eliminating subjective influences. To overcome this, smart devices utilizing inertial measurement unit sensors and artificial intelligence (AI)‐based methods are being developed.MethodsWe employed cutting‐edge technologies, including the smart insole device and pose estimation based on AI, along with three classification models: random forest (RF), support vector machine and artificial neural network, to classify control and sarcopenia groups. Patient data of 83 individuals were divided into train and test sets, with approximately 67% allocated for training. Classification models were implemented using RStudio, considering individual and combined variables obtained through pose estimation and smart insole measurements.ResultsPerformance evaluation of the classification models utilized accuracy, precision, recall and F1‐score indicators. Using only pose estimation variables, accuracy ranged from 0.92 to 0.96, with F1‐scores of 0.94–0.97. Key variables identified by the RF model were ‘Hip_dif’, ‘Ankle_dif’ and ‘Hipankle_dif’. Combining variables from both methods increased accuracy to 0.80–1.00, with F1‐scores of 0.73–1.00.ConclusionsIn our study, a classification model that integrates smart insole and pose estimation technology was assessed. The RF model showed impressive results, particularly in the case of the Hip and Ankle variables. The growth of advanced measurement technologies suggests a promising avenue for identifying and utilizing additional digital biomarkers in the management of various disorders. The convergence of AI technologies with diagnostics and treatment approaches a promising future for enhanced interventions in conditions like sarcopenia.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis

Kim,

Yoo

2023

J cachexia sarcopenia muscle

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“…Vicon is still one of the main optoelectronic motion capture tridimensional systems based on markers [ 6 ], and traditionally has been used for the analysis of biomechanics, gait and robotics [ 64 ]. It is a precision system that analyses motion through video and it is controlled by a computer allowing the analysis of the dysfunctions of the human corporal dynamics [ 65 ].…”

Section: Discussionmentioning

confidence: 99%

Review on Mandibular Muscle Kinematics

Martínez-Silva

Pérez

2022

Sensors

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The complexity of mandibular dynamics encourages constant research as a vehicle to improve oral health. The gold standard motion capture system might help us to understand its functioning and its relation to body position, aiming to perform an exhaustive bibliographic review in the Dentistry field. Six different electronic databases were used (Dentistry & Oral Sciences Source, Scopus, Web of Science, PubMed, CINAHL and SPORTDiscus) in April 2022. The selection criteria includes a biography, critical analysis, and the full text from 1984 to April 2022, based on the odontological gold standard, whether or not in combination with additional devices. Clinical cases, bibliographic reviews or meta-analysis and grey literature were excluded. The checklist of the critical assessment methodology by Joanna Brigs was used (JBI). After choosing scientific articles published in peer-reviewed journals, 23 out of 186 investigations were classified as eligible with a total of 384 participants. The issue being addressed is related to the speech properties, posture and body movement in relation to dento-oro-facial muscle and facial analysis, mandibular kinematics and mandibular dynamics during the mastication process. The markers arrangement depends on the dynamic to be analysed. From a physiologic and pathologic perspective, the applications of the optic system are relevant in Dentistry. The scarcity of literature obtained implies the need for future research.

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“…The Vicon motion capture system (Oxford Metrics Limited, Oxfordshire, United Kingdom) was used to test the 3D gait of the child ( 31 , 32 ), at an acquisition frequency of 100 Hz. A total of 16 markers were fixed to the lower limbs of the child, including 2 markers at the left and right sides of the pelvis, and 1 marker at the left and right side of the knee joint, thigh, calf, ankle joint, toe, and heel.…”

Section: Methodsmentioning

confidence: 99%

Exercise Prescription Improve the Rehabilitation of a Child With Viral Encephalitis Sequelae: A Case Report

et al. 2022

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This study conducted a personalized exercise prescription intervention on a child with viral encephalitis sequelae (VES). The purpose was to observe the rehabilitation process from the aspects of brain activation, and the curative effects on balance function and gait. A further aim was to explore the possible nerve biomechanical mechanisms between the extent of brain activation and the improvement in balance function and gait. A 12-week exercise prescription was used as the treatment method, and functional near-infrared spectroscopy (fNIRS), balance function test system, plantar pressure distribution system, and 3D gait system were used to assess the effects of the rehabilitation process pre and post the intervention. Following the exercise prescription intervention: (1) fNIRS showed that brain activation in the S1–D1, S1–D2, S1–D3, S2–D1, S3–D2, S3–D3, S4–D3, S5–D5, S5–D6, S5–D7, S7–D6, S7–D7, S8–D7, and S8–D8 increased significantly (P < 0.05). (2) The balance test showed that the area of motion ellipse and movement length of the child with eyes open decreased significantly and area of motion ellipse, back and forth swing, left and right swing and movement length of the child with eyes closed all decreased significantly (P < 0.05). (3) The static plantar pressure distribution demonstrated that the pressure center of the left and right foot decreased significantly (P < 0.05) from 5.3° dislocation in a straight line in the sagittal plane to 1°; an increment of the pressure loading was found on the forefoot of both feet compared with what was recorded in the pre-test. (4) The testing results of the 3D gait system showed that she had a shortened time of unilateral support phase and prolonged swing phase on the affected leg (P < 0.05), compared to that of the non-affected leg. Furthermore, the dual support phase had also been prolonged (P < 0.05). Conclusion: 12 weeks’ individualized exercise training can enhance the activation in the motor areas and improve balance function and gait in a child with VES.

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Open source Vicon Toolkit for motion capture and Gait Analysis

Cited by 21 publications

References 15 publications

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis

Sarcopenia classification model for musculoskeletal patients using smart insole and artificial intelligence gait analysis

Review on Mandibular Muscle Kinematics

Exercise Prescription Improve the Rehabilitation of a Child With Viral Encephalitis Sequelae: A Case Report

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