Wearable Hand-Rehabilitation System with Soft Gloves for Patient with Face Paralysis and Disability

Artificially intelligent advances such as tech gloves allow handicapped wearers to handle daily matters as normal. A wearable hand-rehabilitation system, i.e., a robotic arm, is engineered with controlled programming to control a disabled hand with features such as movement of fingers and holding items. A life-threatening disease (stroke) is caused when brain cells start to die, causing around 50–70% of patients to face paralysis and disability. People may face after-effects such as reduced use of the hand and limb or a paralyzed hand. Many methods have been introduced to overcome these issues, including therapies, but they are not so reliable when overcoming disability issues. To overcome these issues, we proposed a smart robotic hand that encounters hand disability issues. The smart robotic hand will aid the hands of disabled people by replacing their disabled hand with the smart robotic hand and by controlling the movement of the robot with the movement of the other hand. This can also be helpful for environments where it is not feasible for humans to work, such as in nuclear reactors and in bomb disposal squads. Some people have disabilities of the hand, so this smart robotic hand can also be used in that scenario. The robotic hand is mainly controlled through a flex sensor. By using Arduino, flex sensor outputs are mapped accordingly to the servo motors. The robot is controlled by a wired arrangement.

Application Of Mirror Therapy On Upper Extremity Motor Recovery In Post-Stroke Patients

Background: Stroke is a health problem for both developed and developing countries, including Indonesia. Paralysis in stroke is mainly due to damage to the internal capsule. This damage requires neuroplasticity involving a number of parts of the brain to restore. One therapy that is beneficial for neuroplasticity is Mirror Therapy (MT). MT is a rehabilitation tool that aims to restore some of the pathological conditions in which the body representation is affected, including post-stroke motor impairment. Methods: This research is a quantitative pre-experimental design with the type one group pretest-postest. The research subjects were 15 post-stroke patients in residency of Semarang. Research data were collected in August-September 2020. Sample selection with purposive sampling technique who conform inclusion criteria. The Fulg-Meyer Upper Extremity Assessment (FMA-UE) as an aoutcame measure that be avowed valid and reliabel. Data analysis using Paired Sample T-Test because of normally distributed. Results: Statistically the results represent a significant difference in the UE motor ability of post-stroke patients between baseline and after mirror therapy intervention, with a mean difference (5,14) and p value = 0.000 (ρ < 0,05). Application of MT effect on upper extremity motor recovery in post-stroke patients. Conclusions: MT program is an effective intervention for UE motor recovery and motor function improvement in post- stroke patients. MT program can be used as a standardized of hand rehabilitation intervention in hospital, clinics and homes.

A Novel Clinical-Driven Design for Robotic Hand Rehabilitation: Combining Sensory Training, Effortless Setup, and Large Range of Motion in a Palmar Device

Neurorehabilitation research suggests that not only high training intensity, but also somatosensory information plays a fundamental role in the recovery of stroke patients. Yet, there is currently a lack of easy-to-use robotic solutions for sensorimotor hand rehabilitation. We addressed this shortcoming by developing a novel clinical-driven robotic hand rehabilitation device, which is capable of fine haptic rendering, and that supports physiological full flexion/extension of the fingers while offering an effortless setup. Our palmar design, based on a parallelogram coupled to a principal revolute joint, introduces the following novelties: (1) While allowing for an effortless installation of the user's hand, it offers large range of motion of the fingers (full extension to 180° flexion). (2) The kinematic design ensures that all fingers are supported through the full range of motion and that the little finger does not lose contact with the finger support in extension. (3) We took into consideration that a handle is usually comfortably grasped such that its longitudinal axis runs obliquely from the metacarpophalangeal joint of the index finger to the base of the hypothenar eminence. (4) The fingertip path was optimized to guarantee physiologically correct finger movements for a large variety of hand sizes. Moreover, the device possesses a high mechanical transparency, which was achieved using a backdrivable cable transmission. The transparency was further improved with the implementation of friction and gravity compensation. In a test with six healthy participants, the root mean square of the human-robot interaction force was found to remain as low as 1.37 N in a dynamic task. With its clinical-driven design and easy-to-use setup, our robotic device for hand sensorimotor rehabilitation has the potential for high clinical acceptance, applicability and effectiveness.

IMPACT OF LEAP MOTION CONTROLLER ON PINCH GRIP IN SUB-ACUTE AND CHRONIC STROKE PATIENTS

Stroke patients have limited everyday tasks. For that videogame-based training (VBT) with the effect of virtual reality helps to improve the role of upper limb and motor function of hand rehabilitation (finger pinch grip). The Leap motion controller can track the both extremities (hand and fingers) fine movements. The study will demonstrate the impact of the leap motion controller on pinch grip in patient with sub-acute and chronic stroke. The total of 40 participants will be taken for study as per inclusion and exclusion criteria. The duration of the study will be six months with intervention. Leap motion -based, augmented reality training will be provided to patients for half hour, Every single day, 5days of the week a month. Formant’s sign and system usability scale will be taken. Those two will be the patient’s measure outcomes. Impact of the leap motion controller device will be evaluated by using the system usability scale and Formant’s sign. The result from the study will significantly provide evidence on the use of Leap motion controller on pinch grip in subacute and chronic stroke patient.

Design and Manufacture of Data Gloves for Rehabilitation Training and Gesture Recognition Based on Flexible Sensors

This work takes the production and usage scenarios of the data glove as the research object and studies the method of applying the flexible sensor to the data glove. Many studies are also devoted to exploring the transplantation of flexible sensors to data gloves. However, this type of research still lacks the display of specific application scenarios such as gesture recognition or hand rehabilitation training. A small amount of experimental data and theoretical analysis are difficult to promote the development of flexible sensors and flexible data gloves design schemes. Therefore, this study uses the self-made flexible sensor of the research group as the core sensing unit to produce a flexible data glove to monitor the bending changes of the knuckles and then use it for simple gesture recognition and rehabilitation training.

An Instrumented Glove-Controlled Portable Hand-Exoskeleton for Bilateral Hand Rehabilitation

Effective bilateral hand training is desired in rehabilitation programs to restore hand function for people with unilateral hemiplegia, so that they can perform daily activities independently. However, owing to limited human resources, the hand function training available in current clinical settings is significantly less than the adequate amount needed to drive optimal neural reorganization. In this study, we designed a lightweight and portable hand exoskeleton with a hand-sensing glove for bilateral hand training and home-based rehabilitation. The hand-sensing glove measures the hand movement of the less-affected hand using a flex sensor. Thereafter, the affected hand is driven by the hand exoskeleton using the measured hand movements. Compared with the existing hand exoskeletons, our hand exoskeleton improves the flexible mechanism for the back of the hand for better wearing experience and the thumb mechanism to make the pinch gesture possible. We designed a virtual reality game to increase the willingness of repeated movement practice for rehabilitation. Our system not only facilitates bilateral hand training but also assists in activities of daily living. This system could be beneficial for patients with hemiplegia for starting correct and sufficient hand function training in the early stages to optimize their recovery.