Posts Tagged Wrist

[Abstract + References] Kineto-static Analysis of a Compact Wrist Rehabilitation Robot Including the Effect of Human Soft Tissue to Compensate for Joint Misalignment


Developing a simple, comfortable rehabilitation robot that can carry out in-home rehabilitation has been a long-time challenge. In this paper, we present a rehabilitation robot with one degree of freedom (DOF) for wrist joint flexion-extension movement. Passive joints have been added to the exoskeleton, forming a four-bar slider crank mechanism, which can reduce unwanted forces due to joint misalignment. A concept of modeling human soft tissue as a passive prismatic joint with spring is introduced in order to achieve the compactness and comfort of the robot simultaneously. In addition, the effects of human soft tissue displacement are compared. A trade-off between robot volume and comfort is discussed. Finally, the kineto-static analysis of the proposed design is conducted to prove the feasibility of adopting this concept in robot-assisted rehabilitation.


  1. 1.Maciejasz, P., Eschweiler, J., Gerlach-Hahn, K., Jansen-Troy, A., Leonhardt, S.: A survey on robotic devices for upper limb rehabilitation. J. Neuroeng. Rehabil. 11(1), 3–31 (2014)CrossRefGoogle Scholar
  2. 2.Norouzi-Gheidari, N., Archambault, P.S., Fung, J.: Effects of robot-assisted therapy on stroke rehabilitation in upper limbs: Systematic review and meta-analysis of the literature. J. Rehabil. Res. Dev. 49(4), 479–496 (2012)CrossRefGoogle Scholar
  3. 3.Ryu, J., Cooney, W.P., Askew, L.J., An, K.-N., Chao, E.Y.S.: Functional ranges of motion of the wrist joint. J. Hand Surg. Am. 16(3), 409–419 (1991)CrossRefGoogle Scholar
  4. 4.Pezent, E., Rose, C.G., Deshpande, A.D., O’Malley, M.K.: Design and characterization of the openwrist: A robotic wrist exoskeleton for coordinated hand-wrist rehabilitation. In: 2017 International Conference on Rehabilitation Robotics (ICORR), pp. 720–725 (2017)Google Scholar
  5. 5.McDaid, A.J.: Development of an Anatomical Wrist Therapy Exoskeleton (AW-TEx). In: 2015 IEEE International Conference on Rehabilitation Robotics (ICORR), pp. 434–439 (2015)Google Scholar
  6. 6.Singh, N., Saini, M., Anand, S., Kumar, N., Srivastava, M.V.P., Mehndiratta, A.: Robotic exoskeleton for wrist and fingers joint in post-stroke neuro-rehabilitation for low-resource settings. IEEE Trans. Neural Syst. Rehabil. Eng. 27(12), 2369–2377 (2019)CrossRefGoogle Scholar
  7. 7.Näf, M.B., Junius, K., Rossini, M., Rodriguez-Guerrero, C., Vanderborght, B., Lefeber, D.: Misalignment compensation for full human-exoskeleton kinematic compatibility: State of the art and evaluation. Appl. Mech. Rev. 70(5), 1–19 (2019)Google Scholar
  8. 8.Liu, Y.-C., Takeda, Y.: Static analysis of a wrist rehabilitation robot with consideration to the compliance and joint misalignment between the robot and human hand. In: Proceedings of Annual Conference of the Robotics Society of Japan 2019, Tokyo (2019)Google Scholar
  9. 9.Liu, Y.-C., Takeda, Y.: Kineto-static analysis of a wrist rehabilitation robot with compliant elements and supplementary passive joints to compensate the joint misalignment. In: The 25th Jc-IFToMM Symposium, Japan (2019)Google Scholar
  10. 10.Xiao, Z.G., Menon, C.: Towards the development of a portable wrist exoskeleton. In: 2011 IEEE International Conference on Robotics and Biomimetics, pp. 1884–1889 (2011)Google Scholar
  11. 11.Takeda, Y., Sugahara, Y., Matsuura, D., Matsuda, S., Suzuki, T., Kitagawa, M., Liu, Y.-C.: Introduction of dynamic pair to modeling and kinemato-dynamic analysis of wearable assist-devices. In: The JSME Annual Mechnical Engineering Congress 2019, Akita, Japan (2019)Google Scholar
  12. 12.Yu, T.F., Wilson, A.J.: A passive movement method for parameter estimation of a musculo-skeletal arm model incorporating a modified hill muscle model. Comput. Methods Programs Biomed. 114(3), e46–e59 (2014)CrossRefGoogle Scholar


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[ARTICLE] Evidence of Neuroplasticity: A Robotic Hand Exoskeleton Study for Post-Stroke Rehabilitation – Full Text PDF


Background: A novel electromechanical robotic-exoskeleton was designed in-house for rehabilitation of wrist joint and Metacarpophalangeal (MCP) joint.

Objective: The objective was to compare the rehabilitation effectiveness (clinical-scales and neurophysiological-measures) of robotic-therapy training-sessions with dose-matched control in patients with stroke.

Methods: An observational pilot study was designed with patients within 2 years of chronicity. Patients received an intervention of 20 sessions of 45-minutes each, five days a week for four-weeks) in Robotic-therapy Group (RG) (n=12) and conventional upper-limb rehabilitation in Control-Group (CG) (n=11). Clinical-scales– Modified Ashworth Scale, Active Range of Motion, Barthel-Index, Brunstrom-stage and Fugl-Meyer scale (Shoulder/Elbow and Wrist/Hand component), and neurophysiological-measures of cortical-excitability (using Transcranial Magnetic Stimulation) –Motor Evoked Potential and Resting Motor-threshold, were acquired pre and post-therapy.

Results: RG and CG showed significant improvement in all clinical motor-outcomes (p<0.05) except Modified Ashworth Scale in CG. RG showed significantly higher improvement over CG in Modified Ashworth Scale, Active Range of Motion and Fugl-Meyer (FM) scale and FM Wrist-/Hand component) (p<0.05). Increase in cortical-excitability in ipsilesional-hemisphere was found to be statistically significant in RG over CG, as indexed by decrease in Resting Motor-Threshold and increase in amplitude of Motor Evoked Potential (p<0.05). No significant changes were shown by the contralesional-hemisphere. Interhemispheric RMT-asymmetry evidenced significant changes in RG over CG (p<0.05) indicating increased cortical-excitability in ipsilesional-hemisphere along with interhemispheric changes.

Conclusion: Neurophysiological-changes in RG could be most likely a consequence of plastic-reorganization and use-dependent plasticity. Robotic-exoskeleton training could significantly improve motor-outcomes and cortical-excitability in patients with stroke.

1. Introduction

Stroke is one of the leading causes of mortality and morbidity worldwide (1). The ability to actively initiate extension movements at wrist and fingers against flexor-hypertonia is one of the key indicators of motor recovery (2),(3). Regaining hand-function and Activities of daily-living (ADL) is particularly impervious to therapy or rehabilitation pertaining to the complexity of motor-control needed for distal-joints (4). Conventional rehabilitation-therapy is time taking, labour-intensive and subjective, which with high clinical-load and absence of skilled resources gets difficult for the present medical and healthcare-system to provide appropriate or effective rehabilitation services (5).

Although rehabilitation with neuro-rehabilitation robots has shown encouraging clinical-results (5, 6, 15, 7–14), it is currently limited to a very few hospitals and not widely used because of associated high-cost and an infrastructural-requirement to station, size, complexity, set-up time, safety and usability restricting its success (16),(17),(18). Rehabilitation-strategies need to take into account the multifaceted nature of disability, which itself changes with time elapsed post-stroke and address with a multimodal-approach. Hence, the device needs to be flexible enough to accommodate a large patient-population. An effective rehabilitation device for hand should be able to facilitate a specific pattern of movements mirroring complex inter-joint coordination of hand with a patient-specific impairment, currently not integrated by the available devices.

In our previous work, we designed a robotic-hand exoskeleton for rehabilitation of the wrist and MCP (Metcarpo-phallengeal) joint, to synchronize wrist-extension with finger-flexion and wrist-flexion with finger-extension, mimicking ADL (19). With simple and easy-to-operate exoskeleton for low-resource settings, the exoskeleton targets spasticity through a synergy-based rehabilitation approach while also maintaining patient-initiated therapy through residual muscle-activity for maximizing voluntary effort. The lightweight and portable device has shown evidence of improvement in quantitative motor clinical-outcomes in patients with chronic stroke (19).

The aim of the present study was twofold. The first objective was to assess the clinical effectiveness of the novel robotic-exoskeleton device (19) and the second is comparison of its clinical-effectiveness with conventional upper-limb rehabilitation. We hypothesized that the exoskeleton could show higher improvement of distal-function and cortical-excitability in patients with stroke as compared to conventional-rehabilitation.[…]

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[Abstract] Remote self-measurement of wrist range of motion performed on normal wrists by a minimally trained individual using the iPhone level application only demonstrated good reliability in measuring wrist flexion and extension


Study Design

This is a reliability study using the intraclass correlation coefficient.


The purpose of this study was to determine whether an individual with minimal training could use the iPhone Level application to self-measure the range of motion of the forearm and wrist from a remote location.


Forty healthy participants (80 wrists) were measured twice by two examiners using a universal goniometer and the iPhone Level application. After measurement, each participant received a training session in the self-measurement method. They were then asked to perform remote self-measurements two to three days later and report their findings to the examiners using Skype or FaceTime.


SPSS, version 26, was used to run intraclass correlation coefficients using a two-way random analysis at a 95% confidence interval with absolute agreement. Comparisons of single measurements were used to determine reliability. Good inter-rater reliability was found between wrist flexion and extension in all testing conditions. Measurement of active motion in supination, pronation, radial, and ulnar deviation demonstrated moderate reliability compared with the universal goniometer where the measurements were performed by the investigators. Self-measurement of the participant resulted in moderate reliability for supination and poor reliability in pronation, radial, and ulnar deviation.


Some participants found the procedures technologically and perceptually challenging. Anatomical variances, positional requirements, and substitution patterns complicated the process.


The iPhone Level application may be used to perform reliable self-measurements of wrist flexion and extension from a remote location. Further research exploring methods for remote self-measurement is indicated


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


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.


  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
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  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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[ARTICLE] A Spatial-Motion Assist-as-Needed Controller for the Passive, Active, and Resistive Robot-Aided Rehabilitation of the Wrist – Full Text PDF


Demand for robot-assisted therapy has increased at every stage of the neurorehabilitation recovery. This paper presents a controller that is suitable for the assist-as-needed (AAN) training of the wrist when performing the spatial motion. A compact wrist exoskeleton robot is presented to realize the AAN controller. This wrist robot includes series elastic actuators with high torque-to-weight ratios to provide accurate force control required for the AAN controller. In addition to assist-as-needed rehabilitation, the parameters of the AAN controller can be adjusted to deliver passive, active, or resistive rehabilitation. Experimental results demonstrate that the proposed AAN controller can provide the total solution to cover each stage of wrist spatial-motion rehabilitation.

(a) Orientation of the wrist and handlebar (b) Omni-directional stiffness K and omni-directional damping B

(a) Orientation of the wrist and handlebar (b) Omni-directional stiffness K and omni-directional damping B

via (PDF) A Spatial-Motion Assist-as-Needed Controller for the Passive, Active, and Resistive Robot-Aided Rehabilitation of the Wrist

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Noor S Shalal† and Wajdi S Aboud‡

†Biomedical Engineering Department, Al-Nahrain University, Baghdad, Iraq

‡Prosthetics and Orthotics Engineering Department, Al-Nahrain University, Baghdad, Iraq

*Corresponding Author Email:




Several causes may result in motor impairment that affects or causes the motions disabilities of the upper limb, among them are spinal cord injury, stroke and wrist drop. Various causes result in the above conditions, so the need for rehabilitation therapy was of most importance. Generally, the researchers interested in and focus on the designing and construction of the lower limb systems for rehabilitation purposes rather than that for upper limbs. This paper focuses on designing and construction of a low cost, two degree freedom (DOF) (including flexion/extension and adduction/abduction), a portable robotic exoskeleton for wrist rehabilitation which designed and constructed with 3D printer technique using polylactic acid (PLA) material and Solid Works software program and controlled with EMG myoware and gyroscope sensors. A significant accurate range of motion and velocity is provided. Moreover, the proposed design of the robotic exoskeleton is comfort, lightweight, simple and economic as well.

via 04.2020.180.192 – Journal of Mechanical Engineering Research and Developments

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[Abstract + References] Improving wrist imaging through a multicentre educational intervention: The challenge of orthogonal projections

In relation to wrist imaging, the accepted requirement is two orthogonal projections obtained at 90°, each with the wrist in neutral position. However, the literature and anecdotal experience suggests that this principle is not universally applied.

This multiphase study was undertaken across eight different hospitals sites. Compliance with standard UK technique was confirmed if there was a change in ulna orientation between the dorsi-palmar (DP) and lateral wrist projections. A baseline evaluation for three days was randomly identified from the preceding three months. An educational intervention was implemented using a poster to demonstrate standard positioning. To measure the impact of the intervention, further evaluation took place at two weeks (early) and three months (late).

Across the study phases, only a minority of radiographs demonstrated compliance with the standard technique, with an identical anatomical appearance of the distal ulna across the projections. Initial compliance was 16.8% (n = 40/238), and this improved to 47.8% (n = 77/161) post-intervention, but declined to 32.8% (n = 41/125) within three months. The presence of pathology appeared to influence practice, with a greater proportion of those with an abnormal radiographic examination demonstrating a change in ulna appearances in the baseline cohort (p < 0.001) and the late post-intervention group (p = 0.002) but not in the examinations performed two weeks after staff education (p = 0.239).

Assessment of image quality is critical for diagnosis and treatment monitoring. Yet poor compliance with standard anatomical principles was evident. A simple educational intervention resulted in a transient improvement in wrist positioning, but the impact was not sustained over time.

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via Improving wrist imaging through a multicentre educational intervention: The challenge of orthogonal projections – Beverly Snaith, Scott Raine, Lynsey Fowler, Christopher Osborne, Sophie House, Ryan Holmes, Emma Tattersall, Emma Pierce, Melanie Dobson, James W Harcus,

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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.


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[NEWS] Researchers at the UI create robotic rehabilitation device to help increase range of motion in the wrist

Assistant professors in the University of Iowa College of Engineering have developed a robotic device to help people increase their range of motion in the wrist using artificial muscles to increase flexibility.


Caterina Lamuta (left) and Venanzio Cichella (right) pose for a portrait in front of their home on Saturday, April 25, 2020. Both mechanical engineering professors at the University of Iowa, the couple is a part of the team working to create a new robotic rehabilitation device.

Two mechanical-engineering assistant professors at the University of Iowa have created a robotic device to give people with limb impairment a wider range of motion. Right now, the pair is focused on the upper limbs and their first prototype increases mobility in the wrist.

The researchers, Venanzio Cichella and Caterina Lamuta, worked together to develop a flexible, lightweight device that can be powered with a small battery. Lamuta and her students are designing and developing the device itself and Cichella and his student are developing the controls of the device.

The device fits over the hand and wrist like a glove, and uses artificial muscles made from carbon fibers which are strong and flexible, Lamuta said. The muscles can lift 12,600 times their weight, and a lot of these artificial muscles can be used to reproduce the arrangement of human muscle. A small battery can be used to power the device, she said.

“So, the idea is to use this more flexible artificial muscle as an alternative for noisy and heavy traditional actuators like electrical motors or hydraulic or pneumatic actuators,” Lamuta said.

The current prototype can perform a few degrees of wrist extension and flexion, she said, but the researchers are working to increase the motion capabilities of the device.

The actuators the researchers are using are very inexpensive, Cichella said. This allows them to not only create a device that is portable and cheap, he said, but allows them to put more of the actuators in the device.

Related: UI researchers say people with spinal-cord injuries can exercise muscles by electrical stimulation

With so many actuators, the question eventually became how to move each of them in order to get the desired action or movement, he said.

Cichella is developing robust control algorithms that can be implemented in the device. He and his student are developing theoretical tools that will help find the optimal controls for the device, Cichella said, and the goal is to implement the algorithms on the side of the device.

Amid spread of the novel coronavirus, some orders for supplies to build sensors have been delayed and working from home makes it so they can’t use larger machinery in the labs, Lamuta said, so they’re going to have delays in their work.

“Part of our research takes place in the lab, which now is the living room of our house and our students’ houses, and also on paper and pen, so it (the challenge) spans both for theoretical and experimental,” Cichella said.

Two UI Ph.D. students and a visiting scholar from Italy are helping with the development of the algorithms and prototypes of the device.

Thilina Weerakkody, a Ph.D. student, and Carlo Greco, the visiting scholar, are working with Lamuta to develop the device itself.

Weerakkody, who has a background in biomedical-device development, has worked on the device, which is similar to an exoskeleton hand, to control it with external feedback. Now, he’s in the process of developing external sensors for the device, he said.

The first prototype only had a single degree of freedom for the wrist, he added.

“Now in the second prototype, we’ve developed a 3D-printed prototype, so in this phase we are trying to elicit two freedom instances,” Weerakkody said.

Greco helped design the muscle used in the glove, choosing the dimension and length of the muscles and studying the schematics of the wrist, he said. The glove was initially able to move up and down in one motion, Greco said, but now they are working to improve movement in the other direction.

“Our testing now is done on a 3D-printed hand with a forearm and we can measure the displacement of the angle of rotation,” Greco said. “…[If] a person does a motion on his own hand and our hand [should] do the same motion in the same [amount of] time.”

Calvin Kielas-Jensen, a Ph.D. student, has worked with Cichella to develop the control algorithms for the device. They’re working with a motion-capture system to give them submillimeter accuracy for the positions of the wrist.

With a background in electrical engineering, Kielas-Jensen has helped with the electronics in the device. He is providing feedback for what kind of sensors should be used and what kind of algorithms should be used to read the data, Kielas-Jensen added.

“It’s a rehabilitation device, so there are plenty of rehabilitation doctors that say that it’s really good to have people do something with their hands,” he said. “It’s one thing to give a patient a stress ball to squeeze, but it gets tired — it gets boring.”

via Researchers at the UI create robotic rehabilitation device to help increase range of motion in the wrist – The Daily Iowan

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[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.


via An interactive and innovative application for hand rehabilitation through virtual reality: International Journal of Advanced Intelligence Paradigms: Vol 15, No 3

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