Posts Tagged Wrist

[Abstract] Motor skill changes and neurophysiologic adaptation to recovery-oriented virtual rehabilitation of hand function in a person with subacute stroke: a case study.



The complexity of upper extremity (UE) behavior requires recovery of near normal neuromuscular function to minimize residual disability following a stroke. This requirement places a premium on spontaneous recovery and neuroplastic adaptation to rehabilitation by the lesioned hemisphere. Motor skill learning is frequently cited as a requirement for neuroplasticity. Studies examining the links between training, motor learning, neuroplasticity, and improvements in hand motor function are indicated.


This case study describes a patient with slow recovering hand and finger movement (Total Upper Extremity Fugl-Meyer examination score = 25/66, Wrist and Hand items = 2/24 on poststroke day 37) following a stroke. The patient received an intensive eight-session intervention utilizing simulated activities that focused on the recovery of finger extension, finger individuation, and pinch-grasp force modulation.


Over the eight sessions, the patient demonstrated improvements on untrained transfer tasks, which suggest that motor learning had occurred, as well a dramatic increase in hand function and corresponding expansion of the cortical motor map area representing several key muscles of the paretic hand. Recovery of hand function and motor map expansion continued after discharge through the three-month retention testing.


This case study describes a neuroplasticity based intervention for UE hemiparesis and a model for examining the relationship between training, motor skill acquisition, neuroplasticity, and motor function changes. Implications for rehabilitation Intensive hand and finger rehabilitation activities can be added to an in-patient rehabilitation program for persons with subacute stroke. Targeted training of the thumb may have an impact on activity level function in persons with upper extremity hemiparesis. Untrained transfer tasks can be utilized to confirm that training tasks have elicited motor learning. Changes in cortical motor maps can be used to document changes in brain function which can be used to evaluate changes in motor behavior persons with subacute stroke.


via Motor skill changes and neurophysiologic adaptation to recovery-oriented virtual rehabilitation of hand function in a person with subacute stroke: … – PubMed – NCBI


, , , , , , , , , , , ,

Leave a comment

[Abstract] Biomechatronics design of a robotic arm for rehabilitation – IEEE Conference Publication


Rehabilitation is an important process to restore muscle strength and joint’s range of motion. This paper proposes a biomechatronic design of a robotic arm that is able to mimic the natural movement of the human shoulder, elbow and wrist joint. In a preliminary experiment, a subject was asked to perform four different arm movements using the developed robotic arm for a period of two weeks. The experimental results were recorded and can be plotted into graphical results using Matlab. Based on the results, the robotic arm shows encouraging effect by increasing the performance of rehabilitation process. This is proven when the result in degree value are accurate when being compared with the flexion of both shoulder and elbow joints. This project can give advantages on research if the input parameter needed in the flexion of elbow and wrist.

I. Introduction

According to the United Nations (UN), by 2030 the number of people over 60 years will increase by 56 per cent, from 901 million to more than 1.4 billion worldwide [1]. As the number of older persons is expected to grow, it is imperative that government and private health care providers prepare adequate and modern facilities that can provide quality services for the needs of older persons especially in rehabilitation centers. Implementation of robotic technology in rehabilitation process is a modern method and definitely can contribute in this policy and capable in promoting early recovery and motor learning [2]. Furthermore, systematic application of robotic technology can produce significant clinical results in motor recovery of post-traumatic central nervous system injury by assisting in physical exercise based on voluntary movement in rehabilitation [3].

via Biomechatronics design of a robotic arm for rehabilitation – IEEE Conference Publication

, , , , , , , , , , , , ,

Leave a comment

[Abstract] Effect of task specific training and wrist-fingers extension splint on hand joints range of motion and function after stroke


via Effect of task specific training and wrist-fingers extension splint on hand joints range of motion and function after stroke – IOS Press

, , , , , , , , ,

Leave a comment

[THESIS] A home-based functional electrical stimulation system for upper-limb stroke rehabilitation – Abstract


Due to an increased population of stroke patients and subsequent demand on health providers, there is an urgent need for effective stroke rehabilitation technology that can be used in patients’ own homes. Over recent years, systems employing functional electrical stimulation (FES) have shown the ability to provide effective therapy. However, there is currently no low-cost therapeutic system available which simultaneously supplies FES to muscles in the patient’s shoulder, arm and wrist to provide co-ordinated functional movement. This restricts the effectiveness of treatment, and hence the ability to support activities of daily living.

In this thesis a home-based low cost rehabilitation system is developed which substantially extends the current state of art in terms of sensing and control methodologies. In particular, it embeds novel non-contact sensing approaches; the first use of an electrode array within a closed-loop model based control scheme; an interactive task display system; and an integrated learning-based controller for multiple muscles within the upper-limb (UL), which supports co-ordinated tasks. The thesis then focuses on compacting the prototype by upgrading the depth sensor and using embedded systems to transfer it to the home

Currently available home-based systems employing FES for UL rehabilitation are first reviewed in terms of their underlying technology, operation, scope and clinical evidence. Motivated by this, a detailed examination of a prototype system is carried out that combines low cost non-contact sensors with closed-loop FES controllers. Then potential avenues to extend the technology are highlighted, with specific focus given to low-cost non-contact based sensors for the hand and wrist. Sensing approaches are then reviewed and evaluated in terms of their scope to support the intended system requirements. Electrode array hardware is developed in order to provide accurate movement capability. Biomechanical models of the combined stimulated arm and mechanical support are then formulated. Using these, model-based iterative learning control methodologies are then designed and implemented.
The system is evaluated with both unimpaired participants and stroke patients undergoing a course of treatment. Finally, a home-based prototype is developed which integrates and extends the aforementioned components. Results conrm the system’s scope to provide more effective stroke rehabilitation. Based on the achieved results, courses of future work necessary to continue this development are outlined.

Full Text PDF

via A home-based functional electrical stimulation system for upper-limb stroke rehabilitation – ePrints Soton

, , , , , , , , ,

Leave a comment

[WEB SITE] Virtual Reality Training Rivals Conventional Therapy After Stroke

Virtual reality training was as effective as, but not superior to, conventional therapy for improving arm and hand function after stroke when both were added to standard rehabilitation in the subacute phase of stroke recovery, researchers found.

In the phase III VIRTUES study, conducted at five rehabilitation hospitals in Europe, similar and significant improvements from baseline assessments of arm and hand mobility were seen at the end of the 4-week intervention and at 3-month follow-up, but there was no difference between the two groups in the results for any endpoints (P<0.001), Iris Brunner, PhD, of Aarhus University, Hammel Neurocenter in Denmark, and colleagues reported online in Neurology.

“These results suggest that either type of training could be used, depending on what the patient prefers,” Brunner said in a statement. “Virtual reality training may be a motivating alternative for people to use as a supplement to their standard therapy after a stroke.”

Improvement of upper extremity motor function performance on the Action Research Arm Test (ARAT) was similar with the virtual reality and conventional training after the 4-week intervention and at follow-up. Patients in virtual reality training improved their ARAT scores an average of 12 points (21%) from baseline to the postintervention assessment, and 17 points (30%) at 3-month follow-up, while those receiving conventional training improved 13 points (21%) at those respective assessments.

Likewise, no differences were seen between the virtual reality and conventional training groups in secondary endpoints, including the Box and Blocks Test, Functional Independence Measure, and Patient Global Impression of Change assessment.

The study involved 120 patients (average age 62) enrolled between March 2014 and April 2016 who had mild-to-severe upper extremity impairment in their wrists, hands, or upper arms as a result of suffering a stroke an average of one month before the study started.

For the add-on conventional or virtual reality therapy, participants had four to five hour-long training sessions per week for four weeks: 62 received conventional physical and occupational therapy, and 58 received virtual reality training that involved using a screen and gloves with sensors to play games that could be adapted to the person’s abilities.

Level of impairment had no differential effect on outcomes, which were similar for patients with mild/moderate impairment – defined as the ability to extend the wrist at least 20 degrees and the fingers at least 10 degrees from drop hand position – or severe impairment. On ARAT, improvements at 3-month follow-up in the mild/moderate group were 14 points (25%) with virtual reality (VR) training and 13 points (23%) with conventional therapy, while the severe group improved 23 points (40%) with VR and 23 points (40%) with conventional therapy.

While active training time was considerably increased among severely impaired participants using virtual reality training compared to those using conventional training, this was not reflected in a larger improvement in arm motor function, authors wrote. This reflects a study design limitation, they wrote: The addition of a third arm receiving only standard rehabilitation would have helped identify potential benefits of more intensive training and increased training time, as previously reported.

Danielle Levac, MD, PhD, PT, of Northeastern University in Boston, who was not involved in the study, agreed with Brunner and colleagues that future study should apply outcome measures that differentiate between recovery on an impairment level and compensation, given that training intensity within the first few months of a stroke is crucial for maximally exploiting the window of increased plasticity.

Also, neither patient engagement nor motivation — attributes through which VR systems are thought to increase adherence and potentially enhance motor learning — were “subjectively or objectively measured here, which seriously detracts from the author’s conclusions that VR constitutes ‘motivating’ training,” Levac told MedPage Today.

The numerous small studies that have demonstrated benefits of virtual reality training have used specially engineered rehab-specific systems, whereas a recent larger trial in subacute stroke patients that did not find superiority over conventional training used a commercial gaming system.

“It is the low cost and easy accessibility of off-the-shelf gaming systems that have made them so pervasive and attractive in clinical practice, despite the disadvantages for tailoring to individual patient needs noted by the authors,” Levac said.

Robert Teasell MD, of Western University in London, Ontario, and head of the Stroke Rehabilitation Writing Group for the Canadian Stroke Best Practice Recommendations, told MedPage Today that many small trials of virtual reality training have demonstrated a benefit in stroke patients.

“This study is important because it is comparatively larger, employs a multisite design, and has an active control group which gets an equal amount of ‘conventional’ therapy and not just ‘usual care,'” said Teasell, who was not involved in the study. “It demonstrates effectiveness – although not superiority – of virtual reality as a promising adjunct treatment.”

via Virtual Reality Training Rivals Conventional Therapy After Stroke | Medpage Today

, , , , , , , , ,

Leave a comment

[ARTICLE] Design and control of a diagnosis and treatment aimed robotic platform for wrist and forearm rehabilitation: DIAGNOBOT – Full Text

Therapeutic exercises play an important role in physical therapy and rehabilitation. The use of robots has been increasing day by day in the practice of therapeutic exercises. This study aims to design and control a novel robotic platform named DIAGNOBOT for diagnosis and treatment (therapeutic exercise). It has three 1-degree-of-freedom robotic manipulators and a single grasping force measurement unit. It is able to perform flexion–extension and ulnar–radial deviation movements for the wrist and pronation–supination movement for the forearm. The platform has a modular and compact structure and is capable of treating two patients concurrently. In order to control the DIAGNOBOT, an impedance control–based controller was developed for force control, which was required for the exercises, as well as a proportional–integral–derivative controller for position control. To model the resistive exercise, an angle-dependent impedance control method different from traditional methods has been proposed. Experiments were made on five healthy subjects and it has been demonstrated that the proposed robotic platform and its controller can perform therapeutic exercises.

Rehabilitation is a treatment process aimed at helping people with physical or anatomical disabilities. These disabilities might be congenital or may have occurred due to an accident, injury, or illness, and this treatment process aims to help such people achieve the highest possible level of functionality in the medical, vocational, and social spheres. Rehabilitation allows disabled people to participate in life at the highest possible level.1 Due to the increasing world population, the need for rehabilitation is also increasing. Individuals with several limbs injured due to age, war, traffic or work-related accidents, or chronic diseases need rehabilitation to achieve full or partial recovery. A wide range of medical methods and treatments have been developed to refunctionalize these limbs, improve their range of motion (ROM) and muscle strength. Therapeutic exercises, one of these methods, play a crucial role in the process of restoring refunctionality for disabled limbs. Therapeutic exercises have two types: passive and active. These exercises can be performed by a physiotherapist or the patient himself.

There are several difficulties and limitations involved in the rehabilitation process, such as an inadequate number of doctors and physiotherapists per patient in highly populated countries, the difficulties suffered by bedridden and aged patients in reaching hospitals, the cost of the rehabilitation process, the duration of the treatment, and keeping a log and following up on the treatment process. According to a report by the Turkish Ministry of Health, the number of physiotherapists per 100.000 people in Turkey is four.2 The highest number of physiotherapists is in Finland, with 202 physiotherapists per 100.000 people. Because of these reasons, the number of studies on rehabilitation robotics has seen an increase over the last two decades.3

Upper limb rehabilitation robots can be classified in terms of mechanical structure, movement capacity, variety of exercises, and control methods. The existed systems can perform one or some of the following exercises: the passive, the resistive, and the active assistive. The control methods commonly used in robotic rehabilitation are as follows: conventional control approaches, such as proportional–derivative (PD) or proportional–integral–derivative (PID), torque control, admittance control, and impedance control.

The MIT-MANUS is a well-known robotic system used for upper limb rehabilitation.4 The system has 3 degrees of freedom (DOFs) and can perform the passive, the active assistive, and the resistive exercises. The control method of the system is impedance control. Reinkensmeyer et al.5 designed a 4-DOF robot, named Assisted Rehabilitation and Measurement Guide (ARM-Guide), for the rehabilitation of the shoulder and the elbow. PD position control and torque control methods were used in the system. The REHAROB was designed using a 6-DOF industrial robot.6The robot can perform passive exercises for decreasing the spasticity in the shoulder, the elbow, and the forearm. In their study, Fraile et al.7 designed a 2-DOF planar robotic platform, called E2Rebot, for upper limb rehabilitation in patients with neuromotor disability caused by a stroke. Besides these studies, there are many other examples of rehabilitation robots.813

A 6-DOF exoskeleton robot was developed by Nef and Riener14 for the rehabilitation of the elbow and the shoulder. The robot can perform passive- and active-assisted exercises. The control method of the system is admittance and impedance control. The use of such exoskeleton robots in rehabilitation is becoming more and more commonplace, and there are a big number of studies cited in the literature.1529

As seen in the literature, many robots have been developed for the rehabilitation. These robots have some limitations. These limitations are DOF, independency of operating of axes, grasping of end-effector (handle), and inability for diagnosis. First, robotic manipulators have one or more DOFs in a single structure. This leads to limitations both in the control of the system and in the force and torque measurements to be made for each axis for diagnosis. Second, the failure of one of the axis also affects other axes. These robots allow for the treatment of only one patient at the same time. Third, in the previous designs, the patients grasp the end-effector. This way is not effective in stroke patients who cannot grasp. Finally, existed designs are not suitable for diagnosis.

To overcome these limitations, a novel robotic platform has been developed in this study. The developed system called DIAGNOBOT consists of three 1-DOF robotic manipulators and a single grasping force measurement unit. The most important feature of this system is that it can perform diagnosis and treatment simultaneously. For this purpose, it is equipped with sensors and actuators developed in a suitable mechanical structure. The force and torque sensors are located in the direction of movement. The robot manipulators for each movement were placed on a rotating table. Each unit can easily be removed and installed. It ensures that the robotic system is modular and configurable. Because the units are independent of each other, it allows for the treatment of two patients at the same time. Thanks to this design, the failure of a unit does not affect other units. The robot manipulators are designed according to stroke patients and they do not need to grasp manipulators (handles). The developed system can perform flexion–extension and ulnar–radial deviation movements for the wrist, and pronation–supination movement for the forearm. It can perform the passive, isometric, isotonic, and resistive therapeutic exercises. DIAGNOBOT controller has a force-based impedance control structure for the isotonic exercise. For variable resistive exercises, a novel impedance–based control method has been developed. In this method, the force on the end-effector changes depends on the joint angle. Therefore, this new control approximation is called the angle-dependent impedance control. This method’s efficiency has been confirmed through experiments made with five healthy subjects. On the other hand, PID control was used for the passive exercise.

There are two contributions to the literature in this study. The former is the unique design of the robotic platform both diagnosis and treatment for upper limb rehabilitation, the latter is the development of a controller based on angle-dependent impedance control to model resistive exercises. An explanatory video about the developed system can be reached in the link.30

This article is organized as follows: the theory of upper limb rehabilitation is specified first, followed by the mechanical design, electronics hardware, strength and limitations, the dynamics, and the control and operation, respectively. Finally, the results and the conclusion are given.

Therapeutic exercises are performed to improve the strength, endurance, coordination, speed, and skills of the limbs. They can be passive or active and can be performed manually or by an assistive device. Therapeutic exercises are considered as one of the important stages of the physical therapy and rehabilitation. In this study, the therapeutic exercises are performed for the rehabilitation of the wrist and the forearm.

Movements of limbs

The developed rehabilitation robot can perform flexion–extension and ulnar–radial deviation movements for the wrist, and pronation–supination movements for the forearm. The definitions of these movements are given in Figure 1 and explained below.


Figure 1. The movements of the wrist and the forearm.


Continue —>  Design and control of a diagnosis and treatment aimed robotic platform for wrist and forearm rehabilitation: DIAGNOBOT – Mehmet Emin Aktan, Erhan Akdoğan, 2018

, , , , , , ,

Leave a comment

[Abstract+References] Interactive System for Hands and Wrist Rehabilitation – Proceedings of the International Conference on Information Technology & Systems (ICITS 2018)


An Interactive system is presented for the rehabilitation of hands and wrists using the leap motion device and the Unity3D software. Two applications were created with several movements were by programming such as flexion, wrist extension, pronation, supination and adduction. Through the interfaces the users have immersion and perform the exercises correctly because at the end of the game a visual and audible feedback is presented. Five people used the system and then the SEQ usability test was applied with results of 59.6. This indicates that the system has a good acceptance and can be used for rehabilitation.


  1. 1.
    Garg, H.T., Choudhury, Kumar, P., Sabitha, S.: Comparison between significance of usability and security in HCI. In: 3rd International Conference on Computational Intelligence & Communication Technology (CICT), pp. 1–4, Ghaziabad (2017)Google Scholar
  2. 2.
    Xu, Z., Qiu, X., He, J.: A novel multimedia human-computer interaction (HCI) system based on Kinect and depth image understanding. In: International Conference on Inventive Computation Technologies (ICICT), pp. 1–6, Coimbatore (2016)Google Scholar
  3. 3.
    Safaei, A., Wu, Q.M.J.: Evaluating 3D hand motion with a softkinetic camera. In: IEEE International Conference on Multimedia Big Data, pp. 290–291, Beijing (2015)Google Scholar
  4. 4.
    Zhi-heng, W., Jiang-tao, C., Jin-guo, L., Zi-qi, Z.: Design of human-computer interaction control system based on hand-gesture recognition. In: 32nd Youth Academic Annual Conference of Chinese Association of Automation (YAC), pp. 143–147, Hefei (2017)Google Scholar
  5. 5.
    Zhu, H., You, Q., Chen, W.: Target-focused video stabilization for human computer interaction. In: 29th Chinese Control and Decision Conference (CCDC), pp. 7688–7693, Chongqing (2017)Google Scholar
  6. 6.
    Liou, J.C., Lin, W.C., Kong, Y.Y.: Multi-channel module of heart rate and electromyography clinical human-computer interaction system. In: IEEE International Conference on Consumer Electronics – Taiwan (ICCE-TW), pp. 97–98, Taipei (2017)Google Scholar
  7. 7.
    Agrawal, R., Gupta, N.: Real time hand gesture recognition for human computer interaction. In: IEEE 6th International Conference on Advanced Computing (IACC), pp. 470–475, Bhimavaram (2016)Google Scholar
  8. 8.
    Guo, J., Li, N., Guo, S., Gao, J.: A LabVIEW-based human-computer interaction system for the exoskeleton hand rehabilitation robot. In: IEEE International Conference on Mechatronics and Automation (ICMA), pp. 571–576, Takamatsu (2017)Google Scholar
  9. 9.
    Wang, B., McDaid, A., Biglari-Abhari, M., Aw, K.C.: Design and development of a glove for post-stroke hand rehabilitation. In: IEEE International Conference on Advanced Intelligent Mechatronics (AIM), Munich, pp. 1047–1051, Germany (2017)Google Scholar
  10. 10.
    Ganeson, S., Ambar, R., Jamil, M.M.A.: Design of a low-cost instrumented glove for hand rehabilitation monitoring system. In: 6th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), pp. 189–192, Batu Ferringhi (2016)Google Scholar
  11. 11.
    Sayilgan, M.E., Kaplanoğlu, E., Atasoy, A., Kuchimov, S., Özkan, M.: Hand rehabilitation and prosthesis training interface. In: 19th National Biomedical Engineering Meeting (BIYOMUT), pp. 1–6. Istanbul (2015)Google Scholar
  12. 12.
    Rodriguez, A., Li, X., Yu, W.: A 3-D hand rehabilitation system using haptic device. In: 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), pp. 1–6, Mexico City (2015)Google Scholar
  13. 13.
    Fitzgerald, D., Kelly, D., Ward, T., Markham, C., Caulfield, B.: Usability evaluation of e-motion: a virtual rehabilitation system designed to demonstrate, instruct and monitor a therapeutic exercise programme. In: Virtual Rehabilitation, pp. 144–149 (2008)Google Scholar
  14. 14.
    Kalawsky, R.S.: VRUSE–a computerised diagnostic tool: for usability evaluation of virtual/synthetic environment systems. Appl. Ergon. 30, 11–25 (1999)CrossRefGoogle Scholar
  15. 15.
    Gil-Gómez, J.A., Gil-Gómez, H., Lozano-Quilis, J.A., Manzano-Hernández, P., Albiol-Pérez, S., Aula-Valero, C.: SEQ: suitability evaluation questionnaire for virtual rehabilitation systems. In: Application in a Virtual Rehabilitation system for Balance Rehabilitation, 2013 7th International Conference on Pervasive Computing Technologies for Healthcare and Workshops, pp. 335–338, Venice (2013)Google Scholar
  16. 16.
    Pruna, E., Acurio, A., Tigse, J., Escobar, I., Pilatásig, M., Pilatásig, P.: Virtual system for upper limbs rehabilitation in children. In: AVR International Conference on Augmented Reality. Virtual Reality and Computer Graphics, LNCS. Springer, pp. 107–118, Verlag (2017)Google Scholar

via Interactive System for Hands and Wrist Rehabilitation | SpringerLink

, , , , , , , , , ,

Leave a comment

[Abstract] Hybrid impedance control of a robot manipulator for wrist and forearm rehabilitation: Performance analysis and clinical results


Therapeutic exercises play an important role in the physical therapy and the rehabilitation. The exercises that can be assisted by a physiotherapist are increasingly being performed by the rehabilitation robots partially or fully due to their various merits. This study aims to develop a complete rehabilitation system, which consists of a rehabilitation robot, an HMI and a hybrid impedance controller that can model all the therapeutic exercises for an upper limb rehabilitation. The 3-DOF upper limb rehabilitation robot is able to perform the movements of flexion–extension and ulnar–radial deviation for the wrist, and the movement of pronation–supination for the forearm. The experimental studies were conducted with healthy subjects and patients. First, the experiments were done with the healthy subjects to prove the control performance of the robotic system. The results showed that the hybrid impedance controlled robot can perform the therapeutic exercises very successfully. Then, the experimental studies were carried out with the real patients in a clinical environment. At the end of the treatment process, remarkable improvements were observed in terms of the limb force in all of the patients.


via Hybrid impedance control of a robot manipulator for wrist and forearm rehabilitation: Performance analysis and clinical results

, , , , , , , ,

Leave a comment

[WEB SITE] Myomo – My own motion

Even if you haven’t moved your hand and arm in years due to a neuromuscular injury or disease, it is possible the MyoPro® may be able to help you use your arm and hand again.

Myopro 2My Own Motion

Myomo empowers individuals with a neuromuscular condition who have lost movement in a hand and arm to perform activities of everyday life. Myomo offers the MyoPro, a myoelectric elbow/wrist/hand orthosis (powered brace) to support the weak arm and enable patients to move an impaired hand and arm again.  MyoPro is the only product of its kind for people who suffer from debilitating neurological disorders such as brachial plexus injury, brain or spinal cord injury, CVA stroke, multiple sclerosis or amyotrophic lateral sclerosis (ALS).

MyoPro is covered by most commercial insurance companies in the U.S., and by the U.S. Veterans Administration – click here for more information for veterans.[…]


VISIT SITE —>  Home | Myomo

, , , , , , , ,

Leave a comment

[Abstract+References] Motion-Based Serious Games for Hand Assistive Rehabilitation


Cerebral Palsy, trauma, and strokes are common causes for the loss of hand movements and the decrease in muscle strength for both children and adults. Improving fine motor skills usually involves the synchronization of wrists and fingers by performing appropriate tasks and activities. This demo introduces a novel patient-centered framework for the gamification of hand therapies in order to facilitate and encourage the rehabilitation process. This framework consists of an adaptive therapy-driven 3D environment augmented with our motion-based natural user interface. An intelligent game generator is developed, which translates the patient’s gestures into navigational movements with therapy-driven goals, while adapting the level of difficulty based on the patient profile and real-time performance. A comprehensive evaluation and clinical-based assessments were conducted in a local children disability center, and highlights of the results are presented.



via Motion-Based Serious Games for Hand Assistive Rehabilitation

, , , , ,

Leave a comment

%d bloggers like this: