2.Lum, P. S., Burgar, C. G., Shor, P. C., Majmundar, M., Van Der Loos, M.: Robot-ass. movement training compared with conventional therapy techniques for the rehab. of upper limb motor function after stroke. Arc. of Phy. Med. and Rehab. 83(7), 952–959 (2002).Google Scholar
4.Nef, T., Mihelj, M., Kiefer, G., Perndl, C., Muller, R., Riener R.:Armin-Exoskeleton for arm therapy in stroke patients’’, In: 10th Int Conf. on Rehab Robotics, pp: 68–74 (2008).Google Scholar
8.Lum ,P. S., Burgar, C. G., Van Der Loos, M., Shor, P. C., Majmundar ,M., Yap, R..:The MIME robotic system for upper-limb neuro-rehabilitation: results from a clinical trial in subacute stroke, In: IEEE 9th Int. Conf.on Rehabilitation Robotics, pp: 511–514. (2005).Google Scholar
9.Khor, K. X., Chin, P. J. H., Hisyam ,A. R., Yeong, C. F., Narayanan A. L. T., Su,E. L. M.: development of cr2-haptic: a compact and portable rehabilitation robot for wrist and forearm training, In: IEEE Conf. on Biomedical Eng. and Sciences, pp: 424–429 (2014).Google Scholar
12.Allington, J., Spencer, S. J., Klein, J., Buell, M., Reinkensmeyer, D. J., Bobrow, J.:Supinator Extender (sue): A pneumatically actuated robot for forearm/wrist rehabilitation after stroke. In: EMBC, 2011, pp:1579–1582 (2011).Google Scholar
13.Gupta, A., O’Malley, M. K., Patoglu, V., Burgar, C., :Design, control and performance of ricewrist: a force feedback wrist exoskeleton for rehabilitation and training, The Int. J. of Robotics Research 27 (2), 233–251 (2008).Google Scholar
14.Spencer, S. J., Klein, J., Minakata, K., Le, V., Bobrow, J. E., Reinkensmeyer, D. J.,: A low cost parallel robot and trajectory optimization method for wrist and forearm rehabilitation. In:(BioRob 2008), pp: 869–874 (2008).Google Scholar
15.Pehlivan, A., Lee, S., O’Malley, M.: Mechanical design of Ricewrist-s: a WF exoskeleton for stroke and spinal cord injury rehabilitation. In: BIOROB, pp: 1573–1578, (2012).Google Scholar
16.Martinez, J. F., Ng, P., Lu, S., Campagna, M., Celik, O.: Design of wrist gimbal: a forearm and wrist exoskeleton for stroke rehabilitation. In: ICORR, pp: 1–6 (2013).Google Scholar
17.Beekhuis, J. H., Westerveld, A. J., Van der Kooij, H., Stienen, A. H. A.: Design of a self-aligning 3-dof actuated exoskeleton for diagnosis and training of wrist and forearm after stroke, IEEE Int. Conf. on Rehabilitation Robotics, (2013).Google Scholar
18.Omarkulov, N., Telegenov, K., Zeinnullin, M., Tursynbek, I.: Preliminary mechanical design of nu-wrist: a 3 dof self-aligning wrist rehabilitation robot. In: BIOROB, 2016.Google Scholar
19.Dağdelen, M., Sarıgeçili M. İ.: Development of a conceptual model for w/f rehabilitation robot with two degrees of freedom, Advances in Robot Design and Int. Control (2017).Google Scholar
20.Kütük, M. E., Daş M. T., Dülger, L. C.: Forward and inverse kinematic analysis of denso robot. In: AzCIFToMM (2017).Google Scholar
Posts Tagged Fingers
[Abstract] An interactive and innovative application for hand rehabilitation through virtual reality
Physiotherapy has been very monotonous for patients and they tend to lose interest and motivation in exercising. Introducing games with short term goals in the field of rehabilitation is the best alternative, to maintain patients’ motivation. Our research focuses on gamification of hand rehabilitation exercises to engage patients’ wholly in rehab and to maintain their compliance to repeated exercising, for a speedy recovery from hand injuries (wrist, elbow and fingers). This is achieved by integrating leap motion sensor with unity game development engine. Exercises (as gestures) are recognised and validated by leap motion sensor. Game application for exercises is developed using unity. Gamification alternative has been implemented by very few in the globe and it has been taken as a challenge in our research. We could successfully design and build an engine which would be interactive and real-time, providing platform for rehabilitation. We have tested the same with patients and received positive feedbacks. We have enabled the user to know the score through GUI.
[Abstract] Motor Imagery Based Brain-Computer Interface Control of Continuous Passive Motion for Wrist Extension Recovery in Chronic Stroke Patients
- Twenty-one patients successfully recovered active wrist extension.
- Motor imagery based BCI control of wrist CPM training was applied.
- Typical spatial and spectrum patterns of ERD/ERS formed after training.
Motor recovery of wrist and fingers is still a great challenge for chronic stroke survivors. The present study aimed to verify the efficiency of motor imagery based brain-computer interface (BCI) control of continuous passive motion (CPM) in the recovery of wrist extension due to stroke. An observational study was conducted in 26 chronic stroke patients, aged 49.0 ± 15.4 years, with upper extremity motor impairment. All patients showed no wrist extension recovery. A 24-channel highresolution electroencephalogram (EEG) system was used to acquire cortical signal while they were imagining extension of the affected wrist. Then, 20 sessions of BCI-driven CPM training were carried out for 6 weeks. Primary outcome was the increase of active range of motion (ROM) of the affected wrist from the baseline to final evaluation. Improvement of modified Barthel Index, EEG classification and motor imagery pattern of wrist extension were recorded as secondary outcomes. Twenty-one patients finally passed the EEG screening and completed all the BCI-driven CPM trainings. From baseline to the final evaluation, the increase of active ROM of the affected wrists was (24.05 ± 14.46)˚. The increase of modified Barthel Index was 3.10 ± 4.02 points. But no statistical difference was detected between the baseline and final evaluations (P > 0.05). Both EEG classification and motor imagery pattern improved. The present study demonstrated beneficial outcomes of MI-based BCI control of CPM training in motor recovery of wrist extension using motor imagery signal of brain in chronic stroke patients.
[Abstract] An EMG-controlled system combining FES and a soft exoskeleton glove for hand rehabilitation of stroke patients – Conference paper
In this paper, we present the development of a hybrid system which supports an active rehabilitation of the closing and the opening of the hand. The particularity of this system is to combine a soft exoskeleton glove, the SEM Glove™, and functional electrical stimulations (FES) to perform both types of hand movements. The created system is also a suggestion of improvement for the SEM Glove™ that is already commercialized by the BIOSERVO company and usable for hand closing rehabilitation only. In our study, a FES system was associated to this glove in order to provide the missing hand opening rehabilitation. To engage the patient in his rehabilitation, our system is electromyogram (EMG)-controlled and is activated according to the patient movement intentions. EMG signals of the muscles involved in the extension and flexion of the fingers were recorded and then processed in order to detect muscle activations. The control of the different elements of the system was then executed based on the results of this detection. The preliminary results demonstrated that the designed hybrid system shows good performances in detecting correctly the intention of a healthy user. Some improvements could still be made in the signal processing to increase the sensitivity of detection, but we proved that the hybrid system is already operational to assist the hand movements of a healthy user.
[VIDEO] Stroke Rehabilitation: Use of electrical stimulation to help the fingers be able to open and close – YouTube
This video demonstrates how to use FES, Functional Electrical Stimulation, to engage the muscles of the arm to extend and flex the fingers
[Abstract] Research on Hand Function Rehabilitation Training Device Based on Human Multimodal Sensation – Full Text PDF
[Abstract + References] Design of an automatic device for rehabilitation of the fingers of the hand for people with ictus – Full Text PDF
The present research presents the construction of a robotic equipment used in the rehabilitation of the fingers for people after an Ictus, the equipment is constituted by a sliding crank mechanism in connection for each finger independently, the static and dynamic characteristic of the parts were designed with anthropometric measures. In addition, an architecture control based on PID-Fuzzy is proposed that achieves an adaptive control for each patient, which allows to have a software with personalized therapies for each patient, incorporates with a database for recording the stages in their rehabilitation according to the type of motor activity, number of repetitions and execution time; finally, the robotic equipment is evaluated in patients with follow-up in a defined time interval.
Roig U and Leal J 2007 Ictus Diagnóstico y tratamiento de las enfermedades cerebrovasculares 60 753-769 Revista Española de Cardiología
Imperial College London 2017 Average life expectancy set to increase by 2030 (ScienceDaily)
Alberto M 2006 Incidencia y prevalencia de cardiopatía isquémica y enfermedad cerebrovascular en España: revisión sistemática de la literatura (Revista española de salud pública vol 80) pp 05-15
Mutuberria R. and Capote R. 2012 Beneficios del ejercicio físico terapéutico en pacientes con secuelas por enfermedad Revista Cubana de Medicina 51 258-266
MhEducation 2008 Morfología de manos y pies” in Estética de Manos y pies vol 5, ed. MCgrawHill pp 7-13
Mayordomo M 2018 Análisis Dinamométrico de la Mano valores normativos de la población española (Departamento de medicina física y rehabilitación Madrid) pp 46-62
Lee C, Chuang C and Kao C 2004 Conference on Cybernetics and Intelligent System 2 (IEEE) Apply Fuzzy PID Rule to PDA Based Control of Position in Control of Slider Crank Mechanism 508-513
Kao C, Chuang C and Fung R 2006 Mechatronics 16 (Elsevier) The self-tuning PID control in a slider–crank mechanism System by applying particle swarm optimization approach 512-522
[Abstract + References] An Exoskeleton Design Robotic Assisted Rehabilitation: Wrist & Forearm – Conference paper
Robotic systems are being used in physiotherapy for medical purposes. Providing physical training (therapy) is one of the main applications of fields of rehabilitation robotics. Upper-extremity rehabilitation involves shoulder, elbow, wrist and fingers’ actions that stimulate patients’ independence and quality of life. An exoskeleton for human wrist and forearm rehabilitation is designed and manufactured. It has three degrees of freedom which must be fitted to real human wrist and forearm. Anatomical motion range of human limbs is taken into account during design. A six DOF Denso robot is adapted. An exoskeleton driven by a serial robot has not been come across in the literature. It is feasible to apply torques to specific joints of the wrist by this way. Studies are still continuing in the subject.
Remarkable assistive device for weak grip
Is your grip weaker than it should be due to accident, neurological condition or other illness? You can achieve a stronger grip and more power and endurance which you then can use in a very natural way with the Carbonhand.
The Carbonhand is the latest evolution of the original SEM™ Glove (Soft Extra Muscles for You) and is a smart, wearable assistive aid to improve your “grip ability” when this has been weakened by illness or trauma.
The glove mimics the human hand by using artificial tendons, motors and sensors along with some very clever software. This approach is called “mechatronics” by engineers – but what you will care about is the result – a product that can help you can have the power and endurance in your fingers to get back to a more complete life.
Developed and tested by Bioservo Technologies in Sweden, we are providing assessment, support and sales in the UK
Who Should Use it?
The Carbonhand is a medical device designed to be used by any person with a weak grip. It is important that the user is able to move their fingers into a grip and extend the fingers again otherwise the glove can’t help. People may suffer from impaired grip strength for countless reasons, such as muscle and nerve damage, muscle diseases, rheumatism and pain. The Carbonhand strengthens the grip and either compensates where power is lacking or adds extra force and endurance.
GRIP STRENGTH AND ENDURANCE IN A VERY NATURAL WAY
Every year another 60,000 UK stroke survivors will find hand and arm problems limiting their activities. With the total number of UK stroke survivors over 1 millions persons already, this is a challenge for society as a whole, as well as those affected.
When we also consider that Spinal Cord Injury, Peripheral Nerve Injury, Chronic Pain Syndrome and trauma also affect the hands of thousands, isn’t it about time we had efficient and effective aids and rehabilitation tools? And what about conditions like MS, Rheumatoid arthritis and even the effects of ageing that impact so powerfully on quality of life?
The Carbonhand consists of two main parts:
- Glove : The main purpose of the glove is to apply the forces generated by the motors in the control unit and to provide the control unit with sensory input from touch sensors at the fingertips. The forces are applied by artificial tendons that are sewn into the glove along the length of the fingers.
- Control unit : The control unit contains a rechargeable battery power source, one motor for each finger which receives extra force and a micro-controller that controls the SEM™ Glove’s functionality.
Who Should Use it?
The Carbonhand is a medical device designed to be used by any person with a weak grip. People may suffer from impaired grip strength for countless reasons, such as muscle and nerve damage, muscle diseases, rheumatism and pain. The product strengthens the grip and either compensates where power is lacking or adds extra force and endurance.
Who Can’t Use it?
The main reason that the product would be ineffective is a complete paralysis of the hand. The sensors in the fingers respond to the user’s intention and ability to apply pressure to the object being gripped. If the person can’t use the fingers at all, the device cannot sense the users intention.
How Do I Try it?
We first must assess if the device is suitable for you. If it is, we will be able to adjust the settings so they suit your current grip issues. You will wear a snugly fitting glove on your affected hand. The thumb and two fingers have pressure sensors in the tips that are essential to the glove’s function. A cable bundle connects the glove to a control pack that sits, for example, on your belt. Rechargeable batteries deliver around 8 hours use. Because the sensors in the glove operate based on touch pressure, you can wear another protective glove over the Carbonhand if necessary for, let’s say, a particular work situation.
UK Pricing is based on a Euro exchange rate with a system package of a control unit, appropriate size glove, batteries, battery charger and manual currently costing around £6,000. As the price will vary with the exchange rate please check with us for accurate price information.
All UK potential clients will be asked to complete the PRE ASSESSMENT Form here
Cloud-based rehabilitation services for post-stroke hand disability.
Tensor-based pattern recognition technique to detect the real-time condition of patient.
The integration of cloud computing with AR-based rehabilitation system.
Multi-sensory big data oriented tensor approach to handle patient’s collected data.
Given the flexibility and potential of cloud technologies, cloud-based rehabilitation frameworks have shown encouraging results as assistive tools for post-stroke disability rehabilitation exercises and treatment. To treat post-stroke disability, cloud-based rehabilitation offers great advantages over conventional, clinic-based rehabilitation, providing ubiquitous flexible rehabilitation services and storage while offering therapeutic feedback from a therapist in real-time during patients’ rehabilitative movements. With the development of sensory technologies, cloud computing technology integrated with Augmented Reality (AR) may make therapeutic exercises more enjoyable.
To achieve these objectives, this paper proposes a framework for cloud-based rehabilitation services, which uses AR technology along with other sensory technologies. We have designed a prototype of the framework that uses the mechanism of sensor gloves to recognize gestures, detecting the real-time condition of a patient doing rehabilitative exercises. This prototype framework is tested on twelve patients not using sensor gloves and on four patients wearing sensor gloves over six weeks. We found statistically significant differences between the forces exerted by patients’ fingers at week one compared to week six. Significant improvements in finger strength were found after six weeks of therapeutic rehabilitative exercises.
[ARTICLE] Development of the Wrist Rehabilitation Therapy (WRist-T) Device based on Automatic Control for Traumatic Brain Injury Patient – iMEDiTEC 2017 – Full Text
In Malaysia, there are not many physiotherapists (PT) as well as rehabilitation centers. Limb rehabilitation is common in rehabilitation centers which include upper limbs and lower limbs. Generally, for upper limb, wrist, hand and fingers rehabilitation is frequently conducted in the centers by PT. The current scenario in Malaysia for wrist rehabilitation is the PT use conventional method to carry out the rehabilitation
procedures. The problem with this procedures, it is time-consuming as the PT need to attend every patient for about 20-30 minutes. This could also lead to exhaustion both to PT and patients. The session can only be done with the assistance on PT, however, there are many patients could not commit to the therapy session due to logistic and domestic problems. This problem can be greatly solved with rehabilitation robot but the
current product in the market is expensive and not affordable especially for low-income earners family. In this paper, a novel automatic control of wrist rehabilitation therapy; called WRist-T device has been developed. The novelty of the device is three modes of exercises that can be carried out which is the flexion and extension, radial and ulnar deviation and pronation and supination. By using this device, the patient can easily receive physiotherapy session with minor supervision from the physiotherapist at the hospital or rehabilitation center and also can be conducted at patient home.[…]