Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation

Kataria, Suchitra; Ravindran, Vinod

doi:10.1186/s12891-022-05126-x

Cited by 11 publications

(6 citation statements)

References 37 publications

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“…This allowed us to examine and show in this article the whole spectrum of possible solutions within the investigated area. These different chainmail versions we used in the author's hand exoskeleton described in other publications [40,41].…”

Section: Methodsmentioning

confidence: 99%

A Semi-Automated 3D-Printed Chainmail Design Algorithm with Preprogrammed Directional Functions for Hand Exoskeleton

et al. 2022

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The problem of computerising the design and development of 3D-printed chainmail with programmed directional functions provides a basis for further research, including the automation of medical devices. The scope of the present research was focused on computational optimisation of the selection of materials and shapes for 3D printing, including the design of medical devices, which constitutes a significant scientific, technical, and clinical problem. The aim of this article was to solve the scientific problem of automated or semi-automated efficient and practical design of 3D-printed chainmail with programmed directional functions (variable stiffness/elasticity depending on the direction). We demonstrate for the first time that 3D-printed particles can be arranged into single-layer chainmail with a tunable one- or two-directional bending modulus for use in a medical hand exoskeleton. In the present work, we accomplished this in two ways: based on traditional programming and based on machine learning. This paper presents the novel results of our research, including 3D printouts, providing routes toward the wider implementation of adaptive chainmails. Our research resulted in an automated or semi-automated efficient and practical 3D printed chainmail design with programmed directional functions for a wrist exoskeleton with variable stiffness/flexibility, depending on the direction. We also compared two methodologies of planning and construction: the use of traditional software and machine-learning-based software, with the latter being more efficient for more complex chainmail designs.

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Section: Methodsmentioning

confidence: 99%

A Semi-Automated 3D-Printed Chainmail Design Algorithm with Preprogrammed Directional Functions for Hand Exoskeleton

et al. 2022

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“…We can, therefore, conclude that there are relatively few publications on exoskeletons. This factor highlights the need to intensify research and increase the number of scientific publications, especially since the above-mentioned 20 publications included three reviews [20][21][22] and two clinical trials [23,24] but no meta-analyses. In the case of 3D-printed orthoses, only four reviews and nine clinical trials were identified, with no meta-analyses.…”

Section: Exoskeletons As 3d-printed Medical Devicesmentioning

confidence: 99%

Specificity of 3D Printing and AI-Based Optimization of Medical Devices Using the Example of a Group of Exoskeletons

et al. 2023

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Three-dimensional-printed medical devices are a separate group of medical devices necessary for the development of personalized medicine. The present article discusses a modern and specific group of medical devices and exoskeletons, which aims to present our own experiences in the selection of materials, design, artificial-intelligence optimization, production, and testing of several generations of various upper limb exoskeletons when considering the Medical Devices Regulation (MDR) and the ISO 13485 and ISO 10993 standards. Work is underway to maintain the methodological rigor inherent in medical devices and to develop new business models to achieve cost-effectiveness so that inadequate legislation does not stop the development of this group of technologies (3D scanning, 3D printing, and reverse engineering) in the healthcare system. The gap between research and engineering practice and clinical 3D printing should be bridged as quickly and as carefully as possible. This measure will ensure the transfer of proven solutions into clinical practice. The growing maturity of 3D printing technology will increasingly impact everyday clinical practice, so it is necessary to prepare medical specialists and strategic and organizational changes to realize the correct implementation based on the needs of patients and clinicians.

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“…Exoskeletons, 3D printing, and virtual rehabilitation all promise to provide patients with precise, low-cost interventions, but they are still in the early stages of development. Modern simulators, tools, and systems are now part of physical rehabilitation technologies, such as microprocessor-based and computerassisted equipment with real-time monitoring [16]. Robotic rehabilitation devices are gaining popularity in dealing with injuries to the limbs.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence (AI) Powered Precise Classification of Recuperation Exercises for Musculoskeletal Disorders

Ekambaram¹,

Ponnusamy²,

Natarajan³

et al. 2023

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Musculoskeletal pain is one of the significant health issues faced by the Information Technology (IT) industries and health-care professional personnel. The current IT sector requires people working on sitting in one place for long hours (~3-4 hours). This causes severe hip, neck, and shoulder pain and may lead to paralysis. Convergence of a threedimensional (3D) image into a plane-based projection to precisely classify the trunk extension and flexion, wrist extension and flexion exercises posture images. Because the predictions in different planes are incorrectly detected during the convergence process, a deep learning algorithm is a superior technique for improving recognition accuracy and processing speed. 200 image datasets of the wrist, trunk extension, and flexion exercise posture are created at various planes. The proposed deep learning algorithm performance is compared with CNN with accelerometer sensing image data, DNN with RGB images, CNN-GRU with Kinect Depth images, Deep Hybrid CNN with body portion keyframe images, Spatial Transform Networks (STN) with attention-based multi-scale CNN with Grad CAM images. The observation demonstrates the efficiency of these systems in musculoskeletal rehabilitation therapy in that the suggested deep learning-based system successfully identifies the completion of rehabilitation activities with a recognition of training accuracy of 98.12% and validation accuracy of 95%. Our approach can track and enhance the efficiency of patients' rehabilitation training with greater satisfactory precision than some other cutting-edge conventional CNN-based baseline architecture.

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Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation

Cited by 11 publications

References 37 publications

A Semi-Automated 3D-Printed Chainmail Design Algorithm with Preprogrammed Directional Functions for Hand Exoskeleton

A Semi-Automated 3D-Printed Chainmail Design Algorithm with Preprogrammed Directional Functions for Hand Exoskeleton

Specificity of 3D Printing and AI-Based Optimization of Medical Devices Using the Example of a Group of Exoskeletons

Artificial Intelligence (AI) Powered Precise Classification of Recuperation Exercises for Musculoskeletal Disorders

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