Posts Tagged finger

[ARTICLE] Direct Drive Hand Exoskeleton for Robot-assisted Post Stroke Rehabilitation – Full Text PDF

Abstract

This article introduces novel rehabilitation hand module development for the
physiotherapy of the hand of patients suffering from spastic hemiplegia. Spasm is basically a muscle cramp, it practically involves the sudden, unintended and painful contraction of a muscle or muscle group, which is caused by nerve damage resulting from a stroke. Stroke is the main reason for permanent disability in adulthood, and so the social- and medical care systems require a huge amount of healthcare resources due to the inactivity of the patients concerned. The robotically facilitated rehabilitation assists the physicians in providing repeated therapies of great intensity, and so the patients may enjoy the benefits of rehabilitation, while the therapists may reduce their own workload at the same time. Furthermore, the robotic devices offer an objective and reliable opportunity for tracing and accurately assessing the improvement of the patients’ motor skills. This article introduces the electrical- and mechanical design of a therapeutic device and the inverse kinematic and dynamic modules which control this device. The rehabilitation device is capable of moving the thumb, the index-, the middle- and the ring fingers, and allows the rehabilitation of the left- and right hands as well. The device is a completely new design with direct
drive approach and several benefits. It has two components: a planar module with serial kinematics of rotational joints with three degrees of freedom (3DoF RRR), and another module with two degrees of freedom (2DoF). The modules integrated load cells, which are built in between each joint to measure the reaction forces. The 3DoF finger moves the index, the middle and the ring fingers, using a load distributor placed above the fingers. The finger orthoses are connected to the load distributor via magnets. The 2DoF finger moves the thumb performing the opening/closing along the plane tilted in two angles.[…]

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[Abstract + References] Automated Voluntary Finger Lifting Rehabilitation Support Device for Hemiplegic Patients to Use at Home

Abstract

We have been proposing a robotic finger rehabilitation support device for hemiplegic patients that can be used at home. This device instructs a patient to lift a finger voluntarily and provides assistance when the patient is impossible to lift. In previous studies, we have shown an automated evaluation method which monitors the level of involuntary finger movement. However, the detailed procedure of finger rehabilitation has not been clarified. In this paper, we show a practical procedure of finger rehabilitation as well as a hardware design of the device. We also discuss safety issues during finger lift assistance. Our design limits the speed of finger lift so that it avoids unwanted contraction of finger muscles by stretch reflex. Also, the angle of finger lift is limited in our design so that it will not exceed the maximum excursion of an MP joint.

References

1.J. D. Schaechter, “Motor rehabilitation and brain plasticity after hemiparetic stroke”, Progress in Neurobiology, vol. 73, no. 1, pp. 61-72, May 2004.Show Context CrossRef  Google Scholar 2.J. W. Krakauer, “Motor learning: its relevance to stroke recovery and neurorehabilitation”, Current Opinion in Neurology, vol. 19, no. 1, pp. 84, Feb. 2006.Show Context CrossRef  Google Scholar 3.S. Balasubramanian, J. Klein and E. Burdet, “Robot-assisted rehabilitation of hand function”, Current Opinion in Neurology, vol. 23, no. 6, pp. 661-670, Dec. 2010.Show Context CrossRef  Google Scholar 4.L. Bishop, A. M. Gordon and H. Kim, “Hand Robotic Therapy in Children with Hemiparesis: A Pilot Study”, American Journal of Physical Medicine & Rehabilitation, vol. 96, no. 1, pp. 1-7, Jan. 2017.Show Context CrossRef  Google Scholar 5.O. Sandoval-Gonzalez et al., “Design and Development of a Hand Exoskeleton Robot for Active and Passive Rehabilitation”, International Journal of Advanced Robotic Systems, vol. 13, no. 66, pp. 1-12, 2016.Show Context CrossRef  Google Scholar 6.P. Polygerinos, K. C. Galloway, E. Savage, M. Herman, K. O. Donnell and C. J. Walsh, “Soft robotic glove for hand rehabilitation and task specific training”, 2015 IEEE International Conference on Robotics and Automation (ICRA), pp. 2913-2919, 2015.Show Context View Article Full Text: PDF (3804KB) Google Scholar 7.D. Guilherme, N. DeSouza et al., “A pediatric robotic thumb exoskeleton for at-home rehabilitation: The isolated orthosis for thumb actuation (IOTA)”, International Journal of Intelligent Computing and Cybernetics, vol. 7, no. 3, pp. 233-252, 2014.Show Context Google Scholar 8.Y. Furudate, N. Onuki, K. Chiba, Y. Ishida and S. Mikami, “Automated Evaluation of Hand Motor Function Recovery by Using Finger Pressure Sensing Device for Home Rehabilitation”, IEEE BIBE 2018, pp. 207-214, 2018.Show Context View Article Full Text: PDF (500KB) Google Scholar 9.K. Yamamoto, Y. Furudate, K. Chiba, Y. Ishida and S. Mikami, “Home Robotic Device for Rehabilitation of Finger Movement of Hemiplegia Patients”, 2017 IEEE/SICE International Symposium on System Integration, pp. TuE1.3:1-6, 2017.Show Context View Article Full Text: PDF (1305KB) Google Scholar 10.Y. Furudate, K. Yamamoto, K. Chiba, Y. Ishida and S. Mikami, “Quantification Method of Motor Function Recovery of Fingers by Using the Device for Home Rehabilitation”, 2017 IEEE 39th Annual International Conference of the Engineering in Medicine and Biology Society, pp. 3872-3875, 2017.Show Context View Article Full Text: PDF (804KB) Google Scholar 11.K. Chiba et al., “Robotic Finger Rehabilitation Support Device for Home Use – An Analysis of the Effect of Finger Rehabilitation for the Upper Limb Function Recovery”, International Journal of Mechanical Engineering and Robotics Research, vol. 5, no. 4, pp. 288-294, Oct. 2016.Show Context CrossRef  Google Scholar 12.“Joint motion: method of measuring and recording”, Churchill Livingstone, 1965.Show Context Google Scholar 13.S. Werle, J. Goldhahn, S. Drerup, B. R. Simmen, H. Sprott and D. B. Herren, “Age- and Gender-Specific Normative Data of Grip and Pinch Strength in a Healthy Adult Swiss Population”, J Hand Surg Eur Vol, vol. 34, no. 1, pp. 76-84, Feb. 2009.Show Context CrossRef  Google Scholar 14.E. L. Altschuler et al., “Rehabilitation of hemiparesis after stroke with a mirror”, The Lancet, vol. 353, no. 9169, pp. 2035-2036, 1999.Show Context CrossRef  Google Scholar 

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[Abstract + References] Real-Time Evaluation of Hand Motor Function Recovery in Home Use Finger Rehabilitation Device Using Gaussian Process Regression – IEEE Conference Publication

Abstract:Continuous hand rehabilitation after discharge is important for hemiplegic patients to regain an independent finger movement. However, most patients cannot rehabilitate by themselves without therapists. For this problem, robotic rehabilitation has been investigated to support patients even at home. Most of the programs performed by these robots are focusing on the assistance for voluntary movement. However, the approach to the voluntary movement is not enough for regaining dexterous movement. Voluntary suppression of body parts that should not move is important. However, previous studies focusing on voluntary suppression are few. In this paper, we show a detailed program for voluntary suppression rehabilitation. The program is performed by our robotic finger rehabilitation device aiming at home use. In this program, a patient is requested to flex and extend an index finger independently. During moving, individual pressure sensors monitor the other fingers. If the device detects unnecessary movements such as compensatory movement at some fingers, the patient is notified that unnecessary movements are found there. The detection is based on 3σ range of healthy subject’s finger pressure data which was constructed by using Gaussian Process Regression. Through experiments with hemiplegic patients, we have shown that the frequency of deviation of patients’ data from 3σ range of healthy subjects decreases according to the degree of recovery.

References

1.C. L. Jones, F. Wang, R. Morrison, N. Sarkar and D. G. Kamper, “Design and Development of the Cable Actuated Finger Exoskeleton for Hand Rehabilitation Following Stroke”, IEEE/ASME Transactions on Mechatronics, vol. 19, no. 1, pp. 131-140, 2014.Show Context View Article Full Text: PDF (740KB) Google Scholar 2.D. Leonardis et al., “An EMG-Controlled Robotic Hand Exoskeleon for Bilateral Rehabilitation”, IEEE Transactions on Haptics, vol. 8, no. 2, pp. 140-151, 2015.Show Context View Article Full Text: PDF (1941KB) Google Scholar 3.S. Biggar and W. Yao, “Design and Evaluation of a Soft and Wearable Robotic Glove for Hand Rehabilitation”, IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 24, no. 10, pp. 1071-1080, 2016.Show Context View Article Full Text: PDF (1597KB) Google Scholar 4.P. Polygerinos, K. C. Galloway, S. Sanan, M. Herman and C. J. Walsh, “EMG Controlled Soft Robotic Glove for Assistance during Activities of Daily Living”, 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 55-60, 2015.Show Context View Article Full Text: PDF (2640KB) Google Scholar 5.I. Ben Abdallah, Y. Bouteraa and C. Rekik, “Design and Development of 3D Printed Myoelectric Robotic Exoskeleton for Hand Rehabilitation”, International Journal on Smart Sensing and Intelligent Systems, vol. 10, pp. 341-366, 2017.Show Context CrossRef  Google Scholar 6.K. Yamamoto, Y. Furudate, K. Chiba, Y. Ishida and S. Mikami, “Home Robotic Device for Rehabilitation of Finger Movement of Hemiplegia Patients”, 2017 IEEE/SICE International Symposium on System Integration (SII), pp. 300-305, 2017.Show Context View Article Full Text: PDF (1305KB) Google Scholar 7.C. D. Takahashi, L. Der-Yeghiaian, V. Le, R. R. Motiwala and S. C. Cramer, “Robot-based Hand Motor Therapy after Stroke”, Brain, vol. 131, no. Pt 2, pp. 425-437, 2008.Show Context CrossRef  Google Scholar 8.L. Dovat et al., A Technique to Train Finger Coordination and Independence after Stroke, Disability and Rehabilitation:Assistive Technology, vol. 5, no. 4, pp. 279-287, 2010.Show Context Google Scholar 9.Y. Furudate, N. Onuki, K. Chiba, Y. Ishida and S. Mikami, “Automated Evaluation of Hand Motor Function Recovery by Using Finger Pressure Sensing Device for Home Rehabilitation”, 2018 IEEE 18th International Conference on Bioinformatics and Bioengineering (BIBE), pp. 207-214, 2018.Show Context View Article Full Text: PDF (500KB) Google Scholar 10.Y. Furudate, N. Onuki, K. Chiba, Y. Ishida and S. Mikami, “Hand Motor Function Evaluation by Integrating Multi-Tasks Using Home Rehabilitation Device”, 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech), pp. 272-274, 2020.Show Context View Article Full Text: PDF (2090KB) Google Scholar 

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[VIDEO] Therapeutic bottle for wrist/hand/finger movements – YouTube

A plastic bottle, an iron wire, a bolt and a bit of bricolage…

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[ARTICLE] Finger State Progress Model for Virtual Fine Motor Stroke Rehabilitation – Full Text PDF

ABSTRACT

Manual observation in measuring and assessing stroke
patient progress in fine motor rehabilitation will lead to
inconsistencies especially when the patient is evaluated
by different therapists or attends different
rehabilitation facilities. In addition, it also increases
therapist workload if they need to supervise many
patients at the same time. Thus, a model was proposed to
capture finger data from motion sensor device using
Time-Based Simplified Denavit-Heartenberg (TS-DH)
and the Finger State progress (FSP) model. Actual
finger movement was compared with patterns of finger
state for real-time evaluation of finger movement
progress. The model will assist therapists in real-time or
post-exercise evaluation of patient progress and
analysis can be done during stroke rehabilitation
exercise. As a conclusion, the model can be used
efficiently in virtual stroke rehabilitation as real-time
indicator or as a long term analysis to compare prior
progress.[…]

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[ARTICLE] Design, analysis and experiment of finger soft actuator with nested structure for rehabilitation training – Full Text PDF

Abstract

Compared with the rigid hand rehabilitation robot, the soft hand rehabilitation robot has the advantages of good flexibility, which is of great significance to its research. In order to make the soft hand rehabilitation robot have the advantagesof high stiffness and simple manufacturing process, a nested structure is proposed for finger soft actuator in this paper.
The nested structure consists of outer restraint structure and inner core structure. The inner core structure can realize deformation under the action of air pressure. The outer restraint structure can improve bending efficiency by restraining deformation in non-functional direction of inner core structure. On this basis, the processing technology of nested structure is designed, and the effect of structural parameters on performance is analyzed. In order to illustrate the advantages of nested structure, the performance of nested structure and fiber-constrained structure is compared by simulation, which includes bending angle, gripping force and expansion amount (by measuring the deformation of the cross section).
The simulation results show the advantages of the nested structure. A prototype of the soft hand rehabilitation robot is developed with nested structure as finger soft actuator, and the experimental results prove the feasibility of design. The results of this study provide a reference for the structure design of soft hand rehabilitation robot.[…]

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[Abstract + References] Stroke Rehabilitation: Detection of Finger Movements

Abstract

For several stroke cases, rehabilitation focuses on the pincer movements and grasps with the index and thumb fingers. The improvements in the coordination between these fingers guides the recovery of the subject. Obtaining a good measurement of these opening and closing movements is still unsolved, with robotic based high cost solutions. This research includes a preliminary study that analyses the use of tri-axial accelerometers to measure these movements and to evaluate the performance of the subjects. Under certain constraints, the solution has been found valid to detect the finger opening-closing pincer movements.

References

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[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

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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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