Posts Tagged finger

[Abstract + Referrences] Interactive and Assistive Gloves for Post-stroke Hand Rehabilitation – Conference paper

Abstract

The inability to fold fingers and move the wrist due to stroke, cardiovascular injuries or emotional shock is one of the most common illnesses wherein conventional rehabilitation therapies are propitious in functional recovery. However, implementation of these methods is laborious, costly and resource-intensive. The structure of the prevailing healthcare system challenges us to design innovative rehabilitation techniques. A desktop-based interactive hand rehabilitation system is, therefore, developed to ensure a more feasible and cost- effective approach. It will encourage a higher number of participation as it is designed to be interesting and interactive than the traditional physiotherapy sessions. The system uses sensor data from Arduino microcontroller and is programmed in Processing IDE allowing user interaction with a virtual environment. The data is further received in an Android application from where it is stored using ThingSpeak Cloud.

References

  1. 1.Popescu, D., Ivanescu, M., & Popescu, R. (2016). Post-stroke assistive rehabilitation robotic gloves. In 2016 International Conference and Exposition on Electrical and Power Engineering (EPE), IEEE Explore, December 12, 2016.Google Scholar
  2. 2.Fischer, H. C., Triandafilou, K. M., Thielbar, K. O., Ochoa, J. M., Lazzaro, E. D. C., Pacholski, K. A., et al. (2015). Use of a portable assistive glove to facilitate rehabilitation in stroke survivors with severe hand impairment. IEEE Transactions on Neural Systems and Rehabilitation Engineering, 24(3), 344–351.CrossRefGoogle Scholar
  3. 3.Prange, G. B., Hermens, H. J., Schäfer, J., Nasr, N., Mountain, G., Stienen, A. H. A., & Amirabdollahian, F. SCRIPT: TELE-ROBOTICS AT HOME Functional architecture and clinical application. Community Research and Development Information Service (CORDIS), Nov 01, 2011–Dec 31, 2014.Google Scholar
  4. 4.Shin, J.-H., Kim, M.-Y. Ji-Yeong, Lee, Jeon, Suyoung Kim, Y.-J., Lee, S., Seo, B., et al. (2016). Effects of virtual reality-based rehabilitation on distal upper extremity function and health-related quality of life: a single-blinded, randomized controlled trial. Journal of Neuro Engineering and Rehabilitation, 13, 17.CrossRefGoogle Scholar
  5. 5.Patel, D. L., Tapase, H. S., Landge, P. A., More, P. P., & Bagade, A. P. (2008). SMART HAND GLOVES FOR DISABLE PEOPLE. International Research Journal of Engineering and Technology (IRJET), 05(04).Google Scholar
  6. 6.Borghetti, M., Sardini, E., & Serpelloni, M. (2013). Sensorized glove for measuring hand finger flexion for rehabilitation purposes. IEEE Transactions on Instrumentation and Measurement, 62(12), 3308–3314.CrossRefGoogle Scholar
  7. 7.Doukas, C., Maglogiannis, I. (2011). Managing wearable sensor data through cloud computing. In 2011 Third IEEE International Conference on Cloud Computing Technology and Science.Google Scholar

Source: Interactive and Assistive Gloves for Post-stroke Hand Rehabilitation | SpringerLink

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[Abstract] Neural coordination of bilateral power and precision finger movements

Cover imageAbstract

The dexterity of hands and fingers is related to the strength of control by cortico‐motoneuronal connections which exclusively exist in primates. The cortical command is associated with a task‐specific, rapid proprioceptive adaptation of forces applied by hands and fingers to an object. This neural control differs between “power grip” movements (e.g., reach and grasp of a cup) where hand and fingers act as a unity and “precision grip” movements (e.g., picking up a raspberry) where fingers move independently from the hand.

In motor tasks requiring hands and fingers of both sides a “neural coupling” (reflected in bilateral reflex responses to unilateral stimulations) coordinates power grip movements (e.g., opening a bottle). In contrast, during bilateral precision movements, such as playing piano, the fingers of both hands move independently, due to a direct cortico‐motoneuronal control, while the hands are coupled (e.g., to maintain the rhythm between the two sides).

While most studies on prehension concern unilateral hand movements, many activities of daily life are tackled by bilateral power grips where a neural coupling serves for an automatic movement performance. In primates this mode of motor control is supplemented by a system that enables the uni‐ or bilateral performance of skilled individual finger movements.

via Neural coordination of bilateral power and precision finger movements – Dietz – – European Journal of Neuroscience – Wiley Online Library

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[Patent Application] FINGER JOINT REHABILITATION DEVICE – Full Text

Abstract

A finger joint rehabilitation device comprising: at least one of an index finger joint rehabilitation exercise aid part, a middle finger joint rehabilitation exercise aid part, a ring finger joint rehabilitation exercise aid part, a little finger joint rehabilitation exercise aid part and a thumb joint rehabilitation exercise aid part; at least one corrugated tube; one protective brace fixed on a wrist and a palm; and the index finger joint rehabilitation exercise aid part, the middle finger joint rehabilitation exercise aid part, the ring finger joint rehabilitation exercise aid part, the little finger joint rehabilitation exercise aid part and the thumb joint rehabilitation exercise aid part are all provided with the corrugated tube and are all fixed on the protective brace.

Continue —->  FINGER JOINT REHABILITATION DEVICE – BEIJING HENGTONG XINJIA TECHNOLOGY DEVELOPMENT CO, LTD.

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[WEB SITE] DigiTrainer – Video

DigiTrainer is a tool for reducing the muscle tone and increasing mobility in the fingers

DIGITRAINER

SIMPLY EFFECTIVE HAND THERAPY

“The principle of action is unique: It is based on the combination of vibration, movement and pressure. The vibration promotes perception and blood circulation to the hand and fingers. ”

DigiTrainer (formerly RehaDigit) can reduce the muscle tone and increase mobility in the fingers of the hand.
Following a stroke, brain injury or spinal cord injury, for example, the muscles and soft-tissues of the hand can become tight and the sensory pathways disrupted.
In order to recover lost tactile sense and to trigger new movement capabilities, intensive rehabilitation is needed and this should start as soon as possible following the injury.
For example, with a cervical level spinal cord injury it is important to avoid complications by early positioning, stretches and oedema management. The hand is perhaps the most important resource after the brain in these cases so the hands must be kept supple if we are to have a chance of developing functional activities. The DigiTrainer makes intensive rehab possible.
DigiTrainer provides both motor and sensory rehabilitation in a simple and effective manner. Through a series of finger-rolls the patient’s fingers are alternately bent and stretched (flexion/extension of the finger joints). The specially designed motor induces a slight vibration into the hand and this supports the relaxation of the finger muscles.

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Vibration preserves sensory pathways

Vibration preserves sensory pathways

DigiTrainer delivers the following functions

  • works for the left and the right hand

  • adjustable rotation velocity

  • adjustable vibration frequency

  • continues or periodic crescendo and decrescendo vibrations

  • ergonomic hand rest (height adjustable)

  • usage via touch screen

  • therapy time: 5-30 min

  • offer price £2,660 ex VAT and shipping

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INDICATIONS FOR USE

DigiTrainer can be used for the following indications:

  • passive bend and stretch movement of the II-V fingers in the rehabilitation of patients with hemi- and tetraparesis from moderate to strong paresis of the upper extremity

  • for example, after stroke, paraplegia, traumatic brain injury, M. Parkinson or joint injuries

  • for patients without distal activity of the wrist and finger flexors

  • incomplete and complete motoric paraplegia after spinal cord injury

  • for patients with spasticity in arms, low blood circulation and impaired hand mobility

  • for patients with functional loss after injury or surgery

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WHAT IT DOES

DigiTrainer is a CE marked Class II medical device. The items included with the product are 1 DigiTrainer, 2 adapter plates for hand rest (25mm and 20°), 1 power supply and appropriate cable and 1 user manual

Check out the video below to see DigiTrainer in action. The unit accomodates left or right hands of various sizes and allows easy programming via a touch screen interface. The therapist can control the specific nature and speed of the movement as the DigiTrainer stretches and massages the fingers. Integrated vibration relaxes tight fingers in a safe and effective way. DigiTrainer has a unique operating principle – most devices focus on movement whereas DigiTrainer also targets the sensorimotor system. Studies have confirmed the effectiveness of the device.

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CONTRAINDICATIONS

The DigiTrainer is generally a safe product but we recommend initial supervision and guidance is obtained from knowledgeable person

Contraindications for DigiTrainer include patients with:

  • fully developed shoulder-arm syndrome

  • acute arthritis in finger joints, thumb joints and/or wrist

  • severe contractures of the finger joints, thumb joints and/or wrist

  • acute disorders requiring special treatment of fingers or hand (e.g. tendinitis)

  • massively swollen hand

  • allergic exanthema of hand

  • fixed fingers.

Related Research

Stefan Hesse, H Kuhlmann, J Wilk, C Tomelleri and Stephen GB Kirker (2008) “A new electromechanical trainer for sensorimotor rehabilitation of paralysed fingers: A case series in chronic and acute stroke patients”
Journal of NeuroEngineering and Rehabilitation20085:21
DOI: 10.1186/1743-0003-5-21
https://jneuroengrehab.biomedcentral.com/articles/10.1186/1743-0003-5-21

R. Buschfort, J. Brocke, A. Heß, C. Werner, A. Waldner, and Stefan Hesse,
”Arm Studio to intensify upper limb rehabilitation after stroke: Concept, acceptance, utilisation and preliminary clinical results”
J Rehabil Med 2010; 42: 310–314

Stefan Hesse, Anke Heß, Cordula Werner, Nadine Kabbert, Rüdiger Buschfort
“Effect on arm function and cost of robot-assisted group therapy in subacute patients with stroke and a moderately to severely affected arm: a randomized controlled trial”
Clinical Rehabilitation 2014, Vol. 28(7) 637–647
DOI: 10.1177/0269215513516967

A. Waldner, C. Werner, S. Hesse
“Robot assisted therapy in neurorehabilitation”
EUR MED PHYS 2008;44(Suppl. 1 to No. 3)

Visit site —->  DigiTrainer

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[WEB SITE] Physical Therapist From Vive Health Demonstrates 8 Easy Hand & Finger Exercises Using Therapy Putty on YouTube – Video

Losing grip strength is a common byproduct of arthritis and a number of other health issues. Following a fast and simple set of exercises using Therapy Putty can help. Vive Health demonstrates them in a free video that is winning wide praise.

Naples, FL (PRUnderground) February 21st, 2020

Arthritis, age, and many other factors can lead to weakened grip and hand strength. Of course, this has a negative lifestyle impact that can’t be understated. Always on top of providing easy-to-follow and functional wellness tips and products Vive Health recently celebrated the release of a compelling new YouTube video addressing this serious concern, “8 Easy Hand & Finger Exercises Using Therapy Putty” with Karen Miller, PTA doing the instruction and demonstration. Only requiring a few minutes a day, and with Therapy Putty being quite affordable, this is a video that those who are going through hand and finger pain or diminishing coordination should not miss.

“For someone who has arthritis this could be the best four minutes they could ever spend watching our Therapy Putty video,” remarked a spokesperson from Vive Health. “Karen is well spoken and knowledgeable and does an amazing job showing these simple hand and finger exercises.  These exercises can help improve dexterity and fine motor skills, while also reducing or removing stress. They are great for physical therapy, occupational therapy and rehabbing a hand or hands after surgery.”

Vive Health offers premium quality Therapy Putty in a number of different strengths so that they can be used in a progressive way to help regain or build hand and finger strength and coordination. Free shipping is even available for orders over $39 in the United States.

Check out the video here.  Be sure to visit Vive Health’s website at https://www.vivehealth.com for more information.

About Vive Health

We are committed to helping you live better. Whether you are recovering from an injury, managing your health, or caring for a loved one, our mission is to provide you with what you need to feel confident and in control.

We strive to separate from the pack and become your trustworthy and affordable online medical equipment store; providing products that you’d be proud to use yourself, give to your loved ones or patients

 

via Physical Therapist From Vive Health Demonstrates 8 Easy Hand & Finger Exercises Using Therapy Putty on YouTube | PRUnderground

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[Abstract] Wearable Hand Exoskeleton Systems for Virtual Reality and Rehabilitation

Abstract

The aim is to overcome the limitations of conventional systems in terms of both wearability and portability. As the hand receives diverse physical information and manipulates different type of objects, conventional systems contain many sensors and actuators, and are both large and heavy. Thus, hand exoskeleton systems exhibiting high wearability and portability while measuring finger motions and delivering forces would be highly valuable. For VR hand exoskeleton systems, a wearable hand exoskeleton system with force-controllable actuator modules was developed to ensure free finger motion and force mode control. The linkage structure ensures motion with three degrees of freedom (DOF) and provides a large fingertip workspace; the finger postures assumed when interacting with objects are appropriate. A series elastic actuator (SEA) with an actuator and an elastic element was used to fabricate compact actuator modules. Actuator friction was eliminated using a friction compensation algorithm. A proportional differential (PD) controller, optimized by a linear quadratic (LQ) method featuring a disturbance observer (DOB), was used to ensure accurate force mode control even during motion. The force control performance of the actuator module was verified in force generation experiments including stationary and arbitrary end-effector motions. The forces applied to the fingertips, which are the principal parts of the hand that interact with objects, were kinematically analyzed via both simulations and experiments. To overcome the weak point of previous system, a wearable hand exoskeleton system featuring finger motion measurement and force feedback was developed and evaluated in terms of user experience (UX). The finger structures for the thumb, index, and middle fingers, which play important roles when grasping objects, satisfy full range of motion (ROM). The system estimates all joint angles of these three digits using a dedicated algorithm; measurement accuracy was experimentally evaluated to verify system performance. The UX performance was evaluated by 15 undergraduate students who completed questionnaires assessing usability and utilitarian value following trials conducted in the laboratory. All subjects were highly satisfied with both usability and the utilitarian nature of the system, not only because control and feedback were intuitive but also because performance was accurate. For rehabilitation, a highly portable exoskeleton featuring flexion/extension finger exercises was developed. The exoskeleton features two four-bar linkages reflecting the natural metacarpophalangeal (MCP) and proximal phalangeal (PIP) joint angles. During optimization, the design parameters were adjusted to reflect normal finger trajectories, which vary by finger length and finger joint ROM. To allow for passive physical impedance, a spring was installed to generate the forces that guided the fingers. The moments transmitted to the MCP and PIP joints were estimated via finite element method (FEM) analysis and the cross-sectional areas of the links were manually designed by reference to the expected joint moments. Finger motion and force distribution experiments verified that the system guided the fingers effectively, allowed for the desired finger motions, and distributed the required moments to the joints (as revealed by FEM analysis).; This thesis reports the development of hand exoskeleton systems, for use in virtual reality (VR) environments and for hand rehabilitation

via ScholarWorks: Wearable Hand Exoskeleton Systems for Virtual Reality and Rehabilitation

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[Abstract] Robotic Exoskeleton for Wrist and Fingers Joint in Post-Stroke Neuro-Rehabilitation for Low-Resource Settings

Abstract

Robots have the potential to help provide exercise therapy in a repeatable and reproducible manner for stroke survivors. To facilitate rehabilitation of the wrist and fingers joint, an electromechanical exoskeleton was developed that simultaneously moves the wrist and metacarpophalangeal joints.
The device was designed for the ease of manufacturing and maintenance, with specific considerations for countries with limited resources. Active participation of the user is ensured by the implementation of electromyographic control and visual feedback of performance. Muscle activity requirements, movement parameters, range of motion, and speed of the device can all be customized to meet the needs of the user.
Twelve stroke survivors, ranging from the subacute to chronic phases of recovery (mean 10.6 months post-stroke) participated in a pilot study with the device. Participants completed 20 sessions, each lasting 45 minutes. Overall, subjects exhibited statistically significant changes (p < 0.05) in clinical outcome measures following the treatment, with the Fugl-Meyer Stroke Assessment score for the upper extremity increasing from 36 to 50 and the Barthel Index increasing from 74 to 89. Active range of wrist motion increased by 190 while spasticity decreased from 1.75 to 1.29 on the Modified Ashworth Scale.
Thus, this device shows promise for improving rehabilitation outcomes, especially for patients in countries with limited resources.

via Robotic Exoskeleton for Wrist and Fingers Joint in Post-Stroke Neuro-Rehabilitation for Low-Resource Settings – IEEE Journals & Magazine

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[VIDEO] Stroke Rehabilitation: Use of electrical stimulation to help arm and hand recovery

This video demonstrates how to use FES, Functional Electrical Stimulation, to engage the muscles of the arm to extend the fingers.

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[Abstract] Fuzzy sliding mode control of a wearable rehabilitation robot for wrist and finger

Abstract

Purpose

The purpose of this paper is to introduce a new design for a finger and wrist rehabilitation robot. Furthermore, a fuzzy sliding mode controller has been designed to control the system.

Design/methodology/approach

Following an introduction regarding the hand rehabilitation, this paper discusses the conceptual and detailed design of a novel wrist and finger rehabilitation robot. The robot provides the possibility of rehabilitating each phalanx individually which is very important in the finger rehabilitation process. Moreover, due to the model uncertainties, disturbances and chattering in the system, a fuzzy sliding mode controller design method is proposed for the robot.

Findings

With the novel design for moving the DOFs of the system, the rehabilitation for the wrist and all phalanges of fingers is done with only two actuators which are combined in one device. These features make the system a good choice for home rehabilitation. To control the robot, a fuzzy sliding mode controller has been designed for the system. The fuzzy controller does not affect the coefficient of the sliding mode controller and uses the overall error of the system to make a control signal. Thus, the dependence of the controller to the model decreases and the system is more robust. The stability of the system is proved by the Lyapunov theorem.

Originality/value

The paper provides a novel design of a hand rehabilitation robot and a controller which is used to compensate the effects of the uncertain parameters and chattering phenomenon.

via Fuzzy sliding mode control of a wearable rehabilitation robot for wrist and finger | Emerald Insight

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[Abstract] Neural Correlates of Passive Position Finger Sense After Stroke

Background. Proprioception of fingers is essential for motor control. Reduced proprioception is common after stroke and is associated with longer hospitalization and reduced quality of life. Neural correlates of proprioception deficits after stroke remain incompletely understood, partly because of weaknesses of clinical proprioception assessments.

Objective. To examine the neural basis of finger proprioception deficits after stroke. We hypothesized that a model incorporating both neural injury and neural function of the somatosensory system is necessary for delineating proprioception deficits poststroke.

Methods. Finger proprioception was measured using a robot in 27 individuals with chronic unilateral stroke; measures of neural injury (damage to gray and white matter, including corticospinal and thalamocortical sensory tracts), neural function (activation of and connectivity of cortical sensorimotor areas), and clinical status (demographics and behavioral measures) were also assessed.

Results. Impairment in finger proprioception was present contralesionally in 67% and bilaterally in 56%. Robotic measures of proprioception deficits were more sensitive than standard scales and were specific to proprioception. Multivariable modeling found that contralesional proprioception deficits were best explained (r2 = 0.63; P = .0006) by a combination of neural function (connectivity between ipsilesional secondary somatosensory cortex and ipsilesional primary motor cortex) and neural injury (total sensory system injury).

Conclusions. Impairment of finger proprioception occurs frequently after stroke and is best measured using a quantitative device such as a robot. A model containing a measure of neural function plus a measure of neural injury best explained proprioception performance. These measurements might be useful in the development of novel neurorehabilitation therapies.

via Neural Correlates of Passive Position Finger Sense After Stroke – Morgan L. Ingemanson, Justin R. Rowe, Vicky Chan, Jeff Riley, Eric T. Wolbrecht, David J. Reinkensmeyer, Steven C. Cramer, 2019

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