Robotic Arm for Biomedical Applications

Doss, Arockia Selvakumar Arockia; Mishra, Birupakshya; Mohammed, Safal; Lingampally, Pavan Kalyan; Short, Michael

doi:10.1007/978-3-030-84205-5_38

Cited by 1 publication

(1 citation statement)

References 34 publications

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“…This disability leads the patient to depend on caretakers for food and water. The upper-limb rehabilitation robots are widely studied and researched because they are similar to the end-effector robots that are widely used in industries for picking and grasping applications [40][41][42][81][82][83][84][85][86]. 2022) have developed a soft wearable upper limb rehabilitation device using sot pneumatic actuators.…”

Section: Wearable Assistive Mechanisms For Upper-limb Rehabilitation ...mentioning

confidence: 99%

Wearable Assistive Rehabilitation Robotic Devices—A Comprehensive Review

Lingampally,

Ramanathan,

Shanmugam

et al. 2024

Machines

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This article details the existing wearable assistive devices that could mimic a human’s active range of motion and aid individuals in recovering from stroke. The survey has identified several risk factors associated with musculoskeletal pain, including physical factors such as engaging in high-intensity exercises, experiencing trauma, aging, dizziness, accidents, and damage from the regular wear and tear of daily activities. These physical risk factors impact vital body parts such as the cervical spine, spinal cord, ankle, elbow, and others, leading to dysfunction, a decrease in the range of motion, and diminished coordination ability, and also influencing the ability to perform the activities of daily living (ADL), such as speaking, breathing and other neurological responses. An individual with these musculoskeletal disorders requires therapies to regain and restore the natural movement. These therapies require an experienced physician to treat the patient, which makes the process expensive and unreliable because the physician might not repeat the same procedure accurately due to fatigue. These reasons motivated researchers to develop and control robotics-based wearable assistive devices for various musculoskeletal disorders, with economical and accessible solutions to aid, mimic, and reinstate the natural active range of motion. Recently, advancements in wearable sensor technologies have been explored in healthcare by integrating machine-learning (ML) and artificial intelligence (AI) techniques to analyze the data and predict the required setting for the user. This review provides a comprehensive discussion on the importance of personalized wearable devices in pre- and post-clinical settings and aids in the recovery process.

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