Passive Devices for Upper Limb Training

Demers, Marika; Rowe, Justin B.; Procházka, A.

doi:10.1007/978-3-031-08995-4_23

Cited by 2 publications

(2 citation statements)

References 151 publications

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“…The iARM, for example, offers enhanced mobility through a wheelchair-mounted robotic arm, facilitating greater independence for users [4]. Similarly, the WREX and ARMON provide vital support for limb movement, significantly improving the quality of life for patients with severe muscular limitations [5]. In addition to hardware advancements, this review delves into the integration of sophisticated software solutions, specifically the use of ensemble machine learning algorithms to forecast rehabilitation outcomes.…”

Section: Literature Reviewmentioning

confidence: 99%

Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach

Filippis,

Foysal

2024

ABB

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Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.

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Section: Literature Reviewmentioning

confidence: 99%

Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach

Filippis,

Foysal

2024

ABB

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“…Passive energy storage mechanisms utilize elements like springs or moving masses to provide resistance during exercises, as shown in [13]. Examples of passive devices include tone-compensating orthoses and serious game controllers [14,15]. Passive devices offer several advantages for home-based rehabilitation [16].…”

Section: Introductionmentioning

confidence: 99%

Design and Analysis of VARONE a Novel Passive Upper-Limb Exercising Device

Amador,

Castillo Castañeda,

Laribi

et al. 2024

Robotics

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Robots have been widely investigated for active and passive rehabilitation therapy of patients with upper limb disabilities. Nevertheless, the rehabilitation assessment process is often ignored or just qualitatively performed by the physiotherapist implementing chart-based ordinal scales or observation-based measures, which tend to rely on professional experience and lack quantitative analysis. In order to objectively quantify the upper limb rehabilitation progress, this paper presents a noVel pAssive wRist motiOn assessmeNt dEvice (VARONE) having three degrees of freedom (DoFs) based on the gimbal mechanical design. VARONE implements a mechanism of three revolute passive joints with controllable passive resistance. An inertial measurement unit (IMU) sensor is used to quantify the wrist orientation and position, and an encoder module is implemented to obtain the arm positions. The proposed VARONE device can also be used in combination with the previously designed two-DoFs device NURSE (cassiNo-qUeretaro uppeR limb aSsistive dEvice) to perform multiple concurrent assessments and rehabilitation tasks. Analyses and experimental tests have been carried out to demonstrate the engineering feasibility of the intended applications of VARONE. The maximum value registered for the IMU sensor is 36.8 degrees, the minimum value registered is −32.3 degrees, and the torque range registered is around −80 and 80 Nmm. The implemented models include kinematics, statics (F.E.M.), and dynamics. Thirty healthy patients participated in an experimental validation. The experimental tests were developed with different goal-defined exercising paths that the participant had to follow.

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Passive Devices for Upper Limb Training

Cited by 2 publications

References 151 publications

Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach

Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach

Design and Analysis of VARONE a Novel Passive Upper-Limb Exercising Device

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