Clinical 3-D Gait Assessment of Patients With Polyneuropathy Associated With Hereditary Transthyretin Amyloidosis

Vilas-Boas, Miguel; Rocha, Ana Patrícia; Cardoso, Márcio; Fernandes, José Maria; Coelho, Teresa; Cunha, João Paulo Silva

doi:10.3389/fneur.2020.605282

Cited by 6 publications

(5 citation statements)

References 36 publications

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“…The main limitation reported by almost all studies in this group ( n = 4) ( Han, Bie & Nicorici, 2016 ; Vilas-Boas et al, 2019 ; Vilas-Boas et al, 2020 ) was small sample size. This was further associated with the rarity of the diseases, making recruitment of subjects for various disease stages difficult.…”

Section: Resultsmentioning

confidence: 85%

“…SCMoCap in this group was utilised with the intention of monitoring disease progression and planning rehabilitative treatment. All studies used cameras that include depth sensors, three studies used a Kinect v2 ( Carmo Vilas-Boas et al, 2019 ; Vilas-Boas et al, 2019 ; Vilas-Boas et al, 2020 ) and two studies used a Kinect v1 ( Han et al, 2015 ; Han, Bie & Nicorici, 2016 ). Depth sensors were utilised to be comparable to 3D marker-based systems and for studies involving understanding functional workspace ( Han et al, 2015 ; Han, Bie & Nicorici, 2016 ).…”

Section: Resultsmentioning

confidence: 99%

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Healthcare applications of single camera markerless motion capture: a scoping review

Scott

Seyres

Philp

et al. 2022

PeerJ

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Background Single camera markerless motion capture has the potential to facilitate at home movement assessment due to the ease of setup, portability, and affordable cost of the technology. However, it is not clear what the current healthcare applications of single camera markerless motion capture are and what information is being collected that may be used to inform clinical decision making. This review aims to map the available literature to highlight potential use cases and identify the limitations of the technology for clinicians and researchers interested in the collection of movement data. Survey Methodology Studies were collected up to 14 January 2022 using Pubmed, CINAHL and SPORTDiscus using a systematic search. Data recorded included the description of the markerless system, clinical outcome measures, and biomechanical data mapped to the International Classification of Functioning, Disability and Health Framework (ICF). Studies were grouped by patient population. Results A total of 50 studies were included for data collection. Use cases for single camera markerless motion capture technology were identified for Neurological Injury in Children and Adults; Hereditary/Genetic Neuromuscular Disorders; Frailty; and Orthopaedic or Musculoskeletal groups. Single camera markerless systems were found to perform well in studies involving single plane measurements, such as in the analysis of infant general movements or spatiotemporal parameters of gait, when evaluated against 3D marker-based systems and a variety of clinical outcome measures. However, they were less capable than marker-based systems in studies requiring the tracking of detailed 3D kinematics or fine movements such as finger tracking. Conclusions Single camera markerless motion capture offers great potential for extending the scope of movement analysis outside of laboratory settings in a practical way, but currently suffers from a lack of accuracy where detailed 3D kinematics are required for clinical decision making. Future work should therefore focus on improving tracking accuracy of movements that are out of plane relative to the camera orientation or affected by occlusion, such as supination and pronation of the forearm.

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Section: Resultsmentioning

confidence: 85%

Section: Resultsmentioning

confidence: 99%

Healthcare applications of single camera markerless motion capture: a scoping review

Scott

Seyres

Philp

et al. 2022

PeerJ

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“…The objective of this study is to quantitatively characterize the gait pattern of patients with V30M ATTRv amyloidosis, thus providing information for a better understanding of the loss of function and with potential for supporting diagnosis and progression evaluation. To the best of our knowledge this analysis has not yet been reported with patients suffering of V30M ATTRv amyloidosis, with only one study reporting a selection of spatiotemporal and angular parameters obtained with a RGB-D camera [ 20 ] and another using a machine learning model to distinguish between healthy and V30M ATTRv amyloidosis mutation carriers (with or without symptoms), also using gait information recorded with a RGB-D system [ 21 ].…”

Section: Introductionmentioning

confidence: 99%

“…Due to the lack of information in the scientific literature [ 20 ], this study’s objective is to present an ATTRv V30M amyloidosis patients’ gait quantitative characterization over a period of 18 months. Since this is a rare disease, this study is structured as a case series reporting the gait pattern of five V30M ATTRv amyloidosis patients.…”

Section: Introductionmentioning

confidence: 99%

Gait Characterization and Analysis of Hereditary Amyloidosis Associated with Transthyretin Patients: A Case Series

Vilas-Boas

Fonseca

Sousa

et al. 2022

JCM

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Hereditary amyloidosis associated with transthyretin (ATTRv), is a rare autosomal dominant disease characterized by length-dependent symmetric polyneuropathy that has gait impairment as one of its consequences. The gait pattern of V30M ATTRv amyloidosis patients has been described as similar to that of diabetic neuropathy, associated with steppage, but has never been quantitatively characterized. In this study we aim to characterize the gait pattern of patients with V30M ATTRv amyloidosis, thus providing information for a better understanding and potential for supporting diagnosis and disease progression evaluation. We present a case series in which we conducted two gait analyses, 18 months apart, of five V30M ATTRv amyloidosis patients using a 12-camera, marker based, optical system as well as six force platforms. Linear kinematics, ground reaction forces, and angular kinematics results are analyzed for all patients. All patients, except one, showed a delayed toe-off in the second assessment, as well as excessive pelvic rotation, hip extension and external transverse rotation and knee flexion (in stance and swing phases), along with reduced vertical and mediolateral ground reaction forces. The described gait anomalies are not clinically quantified; thus, gait analysis may contribute to the assessment of possible disease progression along with the clinical evaluation.

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“…The achieved results show that a single Kinect can be used to obtain several gait-related spatiotemporal parameters or measures, which can be useful for supporting clinical evaluations. We also explored if there was a statistically significant difference between healthy subjects and/or different groups of vATTR-V30M patients, for each one of the 24 computed parameters [44].…”

Section: Introduction Ereditary Transthyretin Amyloidosis (Vattr-v30mmentioning

confidence: 99%

Supporting the Assessment of Hereditary Transthyretin Amyloidosis Patients Based On 3-D Gait Analysis and Machine Learning

Vilas-Boas

Rocha

Cardoso

et al. 2021

IEEE Trans. Neural Syst. Rehabil. Eng.

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Hereditary Transthyretin Amyloidosis (vATTR-V30M) is a rare and highly incapacitating sensorimotor neuropathy caused by an inherited mutation (Val30Met), which typically affects gait, among other symptoms. In this context, we investigated the possibility of using machine learning (ML) techniques to build a model(s) that can be used to support the detection of the Val30Met mutation (possibility of developing the disease), as well as symptom onset detection for the disease, given the gait characteristics of a person. These characteristics correspond to 24 gait parameters computed from 3-D body data, provided by a Kinect v2 camera, acquired from a person while walking towards the camera. To build the model(s), different ML algorithms were explored: k-nearest neighbors, decision tree, random forest, support vector machines (SVM), and multilayer perceptron. For a dataset corresponding to 66 subjects (25 healthy controls, 14 asymptomatic mutation carriers, and 27 patients) and several gait cycles per subject, we were able to obtain a model that distinguishes between controls and vATTR-V30M mutation carriers (with or without symptoms) with a mean accuracy of 92% (SVM). We also obtained a model that distinguishes between asymptomatic and symptomatic carriers with a mean accuracy of 98% (SVM). These results are very relevant, since this is the first study that proposes a ML approach to support vATTR-V30M patient assessment based on gait, being a promising foundation for the development of a computer-aided diagnosis tool to help clinicians in the identification and follow-up of this disease. Furthermore, the proposed method may also be used for other neuropathies.

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Clinical 3-D Gait Assessment of Patients With Polyneuropathy Associated With Hereditary Transthyretin Amyloidosis

Cited by 6 publications

References 36 publications

Healthcare applications of single camera markerless motion capture: a scoping review

Healthcare applications of single camera markerless motion capture: a scoping review

Gait Characterization and Analysis of Hereditary Amyloidosis Associated with Transthyretin Patients: A Case Series

Supporting the Assessment of Hereditary Transthyretin Amyloidosis Patients Based On 3-D Gait Analysis and Machine Learning

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