[Conference paper] Wrist Rehabilitation Equipment Based on the Fin-Ray® Effect – Abstract + References

Abstract

A swift post-traumatic recovery of upper limbs can be achieved best by means of dedicated rehabilitation equipment. A speedy recovery process ensures the early reintegration of patients into society. The rehabilitation equipment proposed in this paper is conceived for the simultaneous passive mobilization of the radiocarpal, metacarpophalangeal and interphalangeal joints. The paper presents and discusses the construction and actuation system of the equipment. The elements of novelty put forward by this equipment refer to the Fin-Ray® effect underlying the design of the hand support and to its operation by means of a pneumatic muscle – an actuator with inherently compliant behavior. The discussion includes the occurring of hysteresis, and concludes that it does not affect the efficiency of the rehabilitation exercises..

References

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   W2 Wrist CPM. http://qalmedical.com/w2-wrist-cpm-device/. Accessed 10 Sept 2018
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   WaveFlex Hand. http://www.remingtonmedical.com/product/detail/A1. Accessed 20 Sept 2018
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    Petre, I., Deaconescu, A., Sârbu, F., Deaconescu, T.: Pneumatic muscle actuated wrist rehabilitation equipment based on the fin ray principle. Strojniški vestnik J. Mech. Eng. 64(6), 383–392 (2018)Google Scholar
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    Filip, O., Deaconescu, T.: Mathematical modelling of a Fin Ray type mechanism, used in the case of the wrist rehabilitation equipment. In: 4th International Conference on Computing and Solutions in Manufacturing Engineering, Brasov, vol. 94 (2017).  https://doi.org/10.1051/matecconf/20179401006CrossRefGoogle Scholar

via Wrist Rehabilitation Equipment Based on the Fin-Ray® Effect | SpringerLink

[Abstract] Pre-therapeutic Device for Post-stroke Hemiplegic Patients’ Wrist and Finger Rehabilitation

Abstract

Background/Objectives

This paper suggests a pre-therapeutic device for post-stroke hemiplegic patients’ wrist and finger rehabilitation both to decrease and analyze their muscle tones before the main physical or occupational therapy.

Method/Statistical Analysis

We designed a robot which consists of a BLDC motor, a torque sensor, linear motion guides and bearings. Mechanical structure of the robot induces flexion and extension of wrist and finger (MCP) joints simultaneously with the single motor. The frames of the robot were 3D printed. During the flexion/extension exercise, angular position and repulsive torque of the joints are measured and displayed in real time.

Findings

A prototype was 3D printed to conduct preliminary experiment on normal subject. From the neutral joint position (midway between extension and flexion), the robot rotated 120 degrees to extension direction and 30 degrees to flexion direction. First, the subject used the machine with the usual wrist and finger characteristics without any tones. Second, the same subject intentionally gave strength to the joints in order to imitate affected upper limb of a hemiplegic patient. During extension exercise, maximum repulsive torque of the normal hand was 2 Nm whereas that of the firm hand was almost 5 Nm. The result revealed that the device was capable enough to not only rotate rigid wrist and fingers with the novel robotic structure, but also present quantitative data such as the repulsive torque according to the joint orientation as an index of joint spasticity level.

Improvements/Applications

We are planning to improve the system by applying torque control and arranging experiments at hospitals to obtain patients’ data and feedbacks to meet actual needs in the field.

via Indian Journals

[Abstract] Attention-controlled assistive wrist rehabilitation using a low-cost EEG Sensor

Abstract

It is essential to make sure patients be actively involved in motor training using robot-assisted rehabilitation to achieve better rehabilitation outcomes. This paper introduces an attention-controlled wrist rehabilitation method using a low-cost EEG sensor. Active rehabilitation training is realized using a threshold of the attention level measured by the low-cost EEG sensor as a switch for a flexible wrist exoskeleton assisting wrist ?exion/extension and radial/ulnar deviation. We present a prototype implementation of this active training method and provide a preliminary evaluation. The feasibility of the attention-based control was proven with the overall actuation success rate of 95%. The experimental results also proved that the visual guidance was helpful for the users to concentrate on the wrist rehabilitation training; two types of visual guidance, namely looking at the hand motion shown on a video and looking at the user’s own hand, had no significant performance difference; a general threshold of a certain group of users can be utilized in the wrist robot control rather than a customized threshold to simplify the procedure.

via Attention-controlled assistive wrist rehabilitation using a low-cost EEG Sensor – IEEE Journals & Magazine

[ARTICLE] Changes in actual arm-hand use in stroke patients during and after clinical rehabilitation involving a well-defined arm-hand rehabilitation program: A prospective cohort study – Full Text

Abstract

Introduction

Improvement of arm-hand function and arm-hand skill performance in stroke patients is reported by many authors. However, therapy content often is poorly described, data on actual arm-hand use are scarce, and, as follow-up time often is very short, little information on patients’ mid- and long-term progression is available. Also, outcome data mainly stem from either a general patient group, unstratified for the severity of arm-hand impairment, or a very specific patient group.

Objectives

To investigate to what extent the rate of improvement or deterioration of actual arm-hand use differs between stroke patients with either a severely, moderately or mildly affected arm-hand, during and after rehabilitation involving a well-defined rehabilitation program.

Methods

Design: single–armed prospective cohort study. Outcome measure: affected arm-hand use during daily tasks (accelerometry), expressed as ‘Intensity-of arm-hand-use’ and ‘Duration-of-arm-hand-use’ during waking hours. Measurement dates: at admission, clinical discharge and 3, 6, 9, and 12 months post-discharge. Statistics: Two-way repeated measures ANOVAs.

Results

Seventy-six patients (63 males); mean age: 57.6 years (sd:10.6); post-stroke time: 29.8 days (sd:20.1) participated. Between baseline and 1-year follow-up, Intensity-of-arm-hand-use on the affected side increased by 51%, 114% and 14% (p < .000) in the mildly, moderately and severely affected patients, respectively. Similarly, Duration-of-arm-hand-use increased by 26%, 220% and 161% (p < .000). Regarding bimanual arm-hand use: Intensity-of-arm-hand-use increased by 44%, 74% and 30% (p < .000), whereas Duration-of-arm-hand-use increased by 10%, 22% and 16% (p < .000).

Conclusion

Stroke survivors with a severely, moderately or mildly affected arm-hand showed different, though (clinically) important, improvements in actual arm-hand use during the rehabilitation phase. Intensity-of-arm-hand-use and Duration-of-arm-hand-use significantly improved in both unimanual and bimanual tasks/skills. These improvements were maintained until at least 1 year post-discharge.

 

Introduction

After stroke, the majority of stroke survivors experiences significant arm-hand impairments [1, 2] and a decreased use of the paretic arm and hand in daily life [3]. The actual use of the affected hand in daily life performance depends on the severity of the arm-hand impairment [4–6] and is associated with perceived limitations in participation [7, 8]. Severity of arm-hand impairment is also associated with a decrease of health-related quality of life [9], restricted social participation [10], and subjective well-being [11, 12].

Numerous interventions and arm-hand rehabilitation programs have been developed in order to resolve arm-hand impairments in stroke patients [6, 13]. In the Netherlands, a number of stroke units in rehabilitation centres implemented a well-described ‘therapy-as-usual’ arm-hand rehabilitation program, called CARAS (acronym for: Concise Arm and hand Rehabilitation Approach in Stroke)[14], serving a broad spectrum of stroke patients across the full stroke severity range of arm-hand impairments. The arm-hand rehabilitation program has been developed to guide clinicians in systematically designing arm-hand rehabilitation, tailored towards the individual patient’s characteristics while keeping control over the overall heterogeneity of this population typically seen in stroke rehabilitation centres. A vast majority of stroke patients who participated in CARAS improved on arm-hand function (AHF), on arm-hand skilled performance (AHSP) capacity and on (self-) perceived performance, both during and after clinical rehabilitation [15]. The term ‘arm-hand function’ (AHF) refers to the International Classification of Functioning (ICF) [16] ‘body function and structures level’. The term ‘arm-hand skilled performance’ (AHSP) refers to the ICF ‘activity level’, covering capacity as well as both perceived performance and actual arm-hand use [17].

Improved AHF and/or AHSP capacity do not automatically lead to an increase in actual arm-hand use and do not guarantee an increase of performing functional activities in daily life [18–20]. Improvements at function level, i.e. regaining selectivity, (grip) strength and/or grip performance, do not automatically lead to improvements experienced in real life task performance of persons in the post-stroke phase who live at home [18, 21]. Next to outcome measures regarding AHF, AHSP capacity and (self-) perceived AHSP, which are typically measured in controlled conditions, objective assessment of functional activity and actual arm-hand use outside the testing situation is warranted [22, 23].

Accelerometry can be used to reliably and objectively assess actual arm-hand use during daily task performance [24–32]and has been used in several studies to detect arm-hand movements and evaluate arm-hand use in the post-stroke phase [20, 33–35]. Previous studies have demonstrated that, in stroke patients, movement counts, as measured with accelerometers, are associated with the use of the affected arm-hand (Motor Activity Log score) [36, 37] and, at function level, with the Fugl-Meyer Assessment [38]. Next to quantifying paretic arm-hand use, accelerometers have also been used to provide feedback to further enhance the use of the affected hand in home-based situations [39]. Most studies consist of relatively small [27, 30, 40–44] and highly selected study populations [45] with short time intervals between baseline and follow-up measurements. As to our knowledge, only a few studies monitored arm-hand use in stroke patients for a longer period, i.e. between time of discharge to a home situation or till 6 to 12 months after stroke [19, 44, 46]. However, they used a relatively small study sample and their intervention aimed at arm-hand rehabilitation was undefined. Both studies of Connell et al. and Uswatte et al. describe a well-defined arm hand intervention where accelerometry data were used as an outcome measure [27, 47]. However, the study population described by Connell et al. consisted of a relative small and a relative mildly impaired group of chronic stroke survivors. The study population described by Uswatte et al. consisted of a large group of sub-acute stroke patients within strict inclusion criteria ranges [37], who, due to significant spontaneous neurologic recovery within this sub-acute phase, had a mildly impaired arm and hand [48, 49]. This means that the group lacked persons with a moderately to severely affected arm-hand, who are commonly treated in the daily rehabilitation setting.

The course of AHF and AHSP of a broad range of sub-acute stroke patients during and after rehabilitation involving a well-defined arm-hand rehabilitation program (i.e. CARAS) [14] has been reported by Franck et al. [15]. The present paper provides data concerning actual arm-hand use in the same study population, and focuses on two objectives. The first aim is to investigate changes in actual arm-hand use across time, i.e. during and after clinical rehabilitation, within a stroke patient group typically seen in daily medical rehabilitation practice, i.e. covering a broad spectrum of arm-hand problem severity levels, who followed a well-described arm-hand treatment regime. The second aim is to investigate to what extent improvement (or deterioration) regarding the use of the affected arm-hand in daily life situations differs between patient categories, i.e. patients with either a severely, moderately or mildly impaired arm-hand, during and after their rehabilitation, involving a well-defined arm-hand rehabilitation program.[…]

Continue —->  Changes in actual arm-hand use in stroke patients during and after clinical rehabilitation involving a well-defined arm-hand rehabilitation program: A prospective cohort study

Fig 3. Mean values for Intensity-of-arm-hand-use during uptime for subgroups 1, 2 and 3.
T = time; bl = baseline; cd = clinical discharge; m = month; Solid line = subgroup 1; Dotted line = subgroup 2; Dashed line = subgroup 3.
https://doi.org/10.1371/journal.pone.0214651.g003

[Abstract] The SonicHand Protocol for Rehabilitation of Hand Motor Function: a validation and feasibility study

Abstract

Musical sonification therapy is a new technique that can reinforce conventional rehabilitation treatments by increasing therapy intensity and engagement through challenging and motivating exercises. Aim of this study is to evaluate the feasibility and validity of the SonicHand protocol, a new training and assessment method for the rehabilitation of hand function. The study was conducted in 15 healthy individuals and 15 stroke patients. The feasibility of implementation of the training protocol was tested in stroke patients only, who practiced a series of exercises concurrently to music sequences produced by specific movements. The assessment protocol evaluated hand motor performance during pronation/supination, wrist horizontal flexion/extension and hand grasp without sonification. From hand position data, 15 quantitative parameters were computed evaluating mean velocity, movement smoothness and angular excursions of hand/fingers. We validated this assessment in terms of its ability to discriminate between patients and healthy subjects, test-retest reliability and concurrent validity with the upper limb section of the Fugl-Meyer scale (FM), the Functional Independence Measure (FIM) and the Box & Block Test (BBT). All patients showed good understanding of the assigned tasks and were able to correctly execute the proposed training protocol, confirming its feasibility. A moderate-to-excellent intraclass correlation coefficient was found in 8/15 computed parameters. Moderate-to-strong correlation was found between the measured parameters and the clinical scales. The SonicHand training protocol is feasible and the assessment protocol showed good to excellent between-group discrimination ability, reliability and concurrent validity, thus enabling the implementation of new personalized and motivating training programs employing sonification for the rehabilitation of hand function.

via The SonicHand Protocol for Rehabilitation of Hand Motor Function: a validation and feasibility study – IEEE Journals & Magazine

[ARTICLE] Design of a robot-assisted exoskeleton for passive wrist and forearm rehabilitation – Full Text

Abstract

This paper presents a new exoskeleton design for wrist and forearm rehabilitation. The contribution of this study is to offer a methodology which shows how to adapt a serial manipulator that reduces the number of actuators used on exoskeleton design for the rehabilitation. The system offered is a combination of end-effector- and exoskeleton-based devices. The passive exoskeleton is attached to the end effector of the manipulator, which provides motion for the purpose of rehabilitation process. The Denso VP 6-Axis Articulated Robot is used to control motion of the exoskeleton during the rehabilitation process. The exoskeleton is designed to be used for both wrist and forearm motions. The desired moving capabilities of the exoskeleton are flexion–extension (FE) and adduction–abduction (AA) motions for the wrist and pronation–supination (PS) motion for the forearm. The anatomical structure of a human limb is taken as a constraint during the design. The joints on the exoskeleton can be locked or unlocked manually in order to restrict or enable the movements. The parts of the exoskeleton include mechanical stoppers to prevent the excessive motion. One passive degree of freedom (DOF) is added in order to prevent misalignment problems between the axes of FE and AA motions. Kinematic feedback of the experiments is performed by using a wireless motion tracker assembled on the exoskeleton. The results proved that motion transmission from robot to exoskeleton is satisfactorily achieved. Instead of different exoskeletons in which each axis is driven and controlled separately, one serial robot with adaptable passive exoskeletons is adequate to facilitate rehabilitation exercises.

 

How to cite.

Kütük, M. E., Dülger, L. C., and Daş, M. T.: Design of a robot-assisted exoskeleton for passive wrist and forearm rehabilitation, Mech. Sci., 10, 107-118, https://doi.org/10.5194/ms-10-107-2019, 2019.

1 Introduction

Deficiencies in the upper extremities restrain a person’s ability to go about daily life, consequently limiting one’s independence. Therefore, robots are used to perform task-oriented repetitive movements in order to improve motor recovery, muscle strength and movement coordination. Stroke is one of the primary reasons for a decrease in motor function of the upper limbs of human beings. It restricts the daily, social and household activities of the patients. Therefore, rehabilitation therapy is required to recover some of the movement lost (Bayona et al., 2005; Bonita and Beaglehole, 1988; Cramer and Riley, 2008). This is accomplished by a long-term intensive and repetitive rehabilitation period. Traditional therapies not only require great effort but also require the manual assistance of physiotherapists. The one-to-one contact of the therapists with their patients leaves the therapists exhausted. Moreover, therapists have limited abilities with regard to speed, senses, strength, and repeatability.

Robot-aided therapy is a developing part of post-stroke rehabilitation care (Reinkensmeyer et al., 2004). Robotic rehabilitation systems ensure compact therapy which can be applied in repetitive, controllable and accurate manner (Kahn et al., 2006; Marchal-Crespo and Reinkensmeyer, 2009). Robotic devices can provide limitless repeatability for patients thus decreasing the effort that therapists have to make (Kwakkel et al., 2008; Lum et al., 2002). Additionally, patient performance evaluation can easily be monitored and assessed by the therapists to adjust the rest of the required therapy (Celik et al., 2010; Ponomarenko et al., 2014).

The types of exercises are grouped into two branches: active and passive exercises. The subjects move their limbs actively and apply torque and/or force in active exercises. Passive exercises are in contrast to active exercises, in which the subjects remain passive during the exercise while an active device moves the limb. Continuous passive motion (CPM) is generated in this way (Maciejasz et al., 2014).

There is a broad range of robotic systems presented for upper-extremity rehabilitation. The mechanical structure of the rehabilitation robots can be mainly grouped into two parts: “end-effector-based” and “exoskeletons”. MIT-MANUS (Krebs et al., 1998) and MIME (Lum et al., 2002) are included in the first part. End-effector-type robots cover a large workspace without having the capability to apply torques to specific joints of the arm. Having simpler control structure than exoskeletons is an advantage of end-effector-type devices. The most distal part of the robot is in contact with the patient limb. The segments of the upper extremities can be regarded as a mechanical chain. Therefore, motion in the end effector of the robot will automatically move other segments of the patient. They may cause redundant configurations of the patient’s upper extremities and may risk injury. Exoskeletons are the external structural mechanisms that have joints and links that can collaborate with the human body. They transmit motion exerted by the links to the human joints, thus making them suitable for the human anatomy. Exoskeletons must be able to carry out movements within the natural limitations of a human wrist for an ergonomic design. Mechanical and control issues are more complex than end-effector-type devices. The 5 degrees of freedom (DOF) MAHI (Gupta and O’Malley, 2006), 6 DOF ARMin (Nef et al., 2008) and 7 DOF CADEN-7 (Perry et al., 2007) are some examples of exoskeletons used in upper-extremity rehabilitation. LIMPACT (Otten et al., 2015), MIT-Manus (Krebs et al., 1998) and MIME (Lum et al., 2005) are prime examples of systems designed for assisting upper-limb proximal joints (the shoulder and the elbow). On the other hand, CR-2 Haptic (Khor et al., 2014) has one rotational DOF. There are manual reconfigurations for any specific wrist movement. Systems called Universal Haptic Drive (Oblak et al., 2010), Bi-Manu-Track (Lum et al., 1993) and Supinator Extender (Allington et al., 2011) have 2 DOF. The closest configuration resembling a human wrist and a rehabilitation robot can be employed by a 3 DOF system with three revolute joints. This configuration type enhances the functionality of devices providing rehabilitation services as it allows independence for specific motions of the wrist. RiceWrist (Gupta et al., 2008) and CRAMER (Spencer et al., 2008) use parallel mechanisms for wrist and forearm rehabilitation. RiceWrist-S (Pehlivan et al., 2012) is a 3 DOF exoskeleton system which is the developed version of RiceWrist (Gupta et al., 2008). A three-axis gimbal called WristGimbal (Martinez et al., 2013) offers flexibility to adjust rotation centers of the axes in order to match the wrist center of the patient. A 3 DOF self-aligning exoskeleton given in Beekhuis et al. (2013) compensates for misalignment of the wrist and forearm. Parallelogram linkages are used for this purpose. Nu-Wrist (Omarkulov et al., 2016) is a novel self-aligning 3 DOF system allowing passive adaptation in the wrist joint.

This paper presents the design of an exoskeleton for human wrist and forearm rehabilitation. Specific wrist and forearm therapies are performed. An issue with the angular displacement limit of a robot axis was experienced. The solution method obtained by changing the design is given herein. Adapting a 6 DOF Denso robot for wrist and forearm rehabilitation is proposed. The novelty of the study is the use of an exoskeleton driven by a serial robot, which is a method that has not yet been tackled in the literature. The proposed system hybridized the end-effector-type and exoskeleton-type rehabilitation systems in order to utilize advantages and to avoid disadvantages. Precise movement transmission from robot to patient limb can be provided by using an exoskeleton which plays a guide role in the exercises. This adaptation makes the system feasible to apply torques to specific joints of the wrist and allow independent, concurrent and precise movement control. This technique offers flexibility to the users. If the user wants wrist and forearm rehabilitation, a 3-D model of the exoskeleton is designed, manufactured with 3-D printing technology and interfaced with the robot. The exoskeleton may be designed for ankle, shoulder and/or elbow applications. Therefore, a serial robot can be used as a motion provider for different types of rehabilitation. Instead of different exoskeletons having a motor for each axis, the combination of a serial robot and passive exoskeleton is enough to perform the rehabilitation exercises.

2 Wrist and forearm motion and exoskeleton design

A human uses the distal parts of his/her arm (i.e., wrist, forearm) in coordination with proximal parts (i.e., elbow, shoulder) in order to carry out movements required in daily life, e.g., wrist and forearm motions such as eating, writing, opening a door, driving an automobile and so on. The wrist joint has got 2 DOF; flexion and extension (FE) and radial–ulnar deviation. Radial–ulnar deviations can also be called adduction and abduction (AA), respectively. Flexion is the bending of the wrist so that the palm approaches the anterior surface of the forearm. The extension is the reverse of flexion. Abduction (radial deviation) is the bending of the wrist towards to the thumb side. The reverse of this motion is called adduction (ulnar deviation). Pronation and supination (PS) are the movements for the forearm. Pronation is applied to a hand such that the palm turns backward or downward. Supination is the rotation of the forearm such that the palm of the hand faces anteriorly to the anatomic position (Omarkulov et al., 2016). These motions are given in Fig. 1.

Figure 1DOF of wrist and forearm (Omarkulov et al., 2016).

[…]

 

Continue —> MS – Design of a robot-assisted exoskeleton for passive wrist and forearm rehabilitation

[Abstract + References] A compact wrist rehabilitation robot with accurate force/stiffness control and misalignment adaptation

Abstract

Robots have been demonstrated to assist the rehabilitation of patients with upper or lower limb disabilities. To make exoskeleton robots more friendly and accessible to patients, they need to be lightweight and compact without major performance tradeoffs. Existing upper-limb exoskeleton robots focus on the assistance of the coarse-motion of the upper arm while the fine-motion rehabilitation of the forearm is often ignored. This paper presents a wrist robot with three degrees-of-freedom. Using a geared bearing, slider crank mechanisms, and a spherical mechanism, this robot can provide the complete motion assistance for the forearm. The optimized robot dimensions allow large torque and rotation output while the motors are placed parallel to the forearm. Thus lightweight, compactness, and better inertia properties can be achieved. Linear and rotary series elastic actuators (SEAs) with high torque-to-weight ratios are proposed to accurately measure and control the interaction force and impedance between the robot and the wrist. The resulting 1.5-kg robot can be used alone or easily in combination with other robots to provide various robot-aided upper limb rehabilitation.

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via A compact wrist rehabilitation robot with accurate force/stiffness control and misalignment adaptation | SpringerLink

[WEB SITE] How to stretch your hands and wrists – Videos

By Adrienne Stinson

Wrist pain can be frustrating and inconvenient. It can also make work or basic day-to-day activities, such as using a computer or cooking a meal, more difficult.

Exercises can improve mobility and decrease the chance of injury or reinjury. Wrist stretches are easy to do at home or at the office. When done properly, they can benefit a person’s overall wrist and hand health.

Anyone experiencing chronic pain or pain with numbness should visit a doctor for a thorough diagnosis.

The following stretches can help improve strength and mobility:

Wrist and hand stretches

A person should do the exercises below slowly and gently, focusing on stretching and strengthening. If the stretch hurts, stop.

The following wrist and hand stretches may improve strength and mobility:

1. Raised fist stretch

To do this stretch:

1. Start with your arm up beside your head, with your hand open.
2. Make a fist, keeping your thumb outside of it.
3. Slide your fingers toward your wrist until you feel a stretch.

2. Wrist rotations

To do this stretch:

1. Stretch your arm out in front of you.
2. Slowly, point the fingers down until you feel a stretch. Use the other hand to gently pull the raised hand toward the body. Hold this position for 3–5 seconds.
3. Point the fingers toward the ceiling until you feel a stretch. Use the other hand to gently pull the raised hand toward the body. Hold this position for 3–5 seconds.
4. Repeat this three times.

3. Prayer position

To do this stretch:

1. Sit with your palms together and your elbows on the table in a prayer position.
2. Lower the sides of the hands toward the table until you feel a stretch. Keep your palms together. Hold this position for 5–7 seconds.
3. Relax.
4. Repeat this three times.

4. Hooked stretch

To do this stretch:

1. Hook one elbow under the other and pull both arms towards the center of the torso. You should feel a stretch in your shoulders.
2. Wrap one arm around the other so that the palms are touching.
3. Hold the position for 25 seconds.
4. Switch arms and repeat it on the other side.

5. Finger stretch

To do this stretch:

1. Bring the pinky and ring fingers together.
2. Separate the middle and index fingers from the ring finger.
3. Repeat the stretch 10 times.

6. Fist-opener

To do this stretch:

1. Make a fist and hold it in front of you.
2. Stretch your fingers until your hand is flat and open, with the fingers together.
3. Repeat the movements 10 times.

7. Sponge-squeeze

To do this stretch:

1. Squeeze a sponge or stress ball, making a fist.
2. Hold the position for 10 seconds.
3. Relax.
4. Repeat this 10 times.

8. Windshield wiper wrist movement

To do this stretch:

1. Start with your hand face down on a table.
2. Gently, point the hand to one side as far as it can go without moving the wrist. Hold it there for 3–5 seconds.
3. Do the same on the other side.
4. Repeat the movement three times on each side.

9. Thumb pull

To do this stretch:

1. Grab your thumb with the other hand.
2. Gently pull the thumb backward, away from the hand.
3. Hold the stretch for 25 seconds.
4. Repeat it on the other thumb.

10. Flower stretch

To do this stretch:

1. Stretch the arms in front of you, with the backs of the hands and wrists touching.
2. Imagine an invisible force pulling the fingers further from the body. Feel the stretch.
3. Hold it for 25 seconds.

11. Finger fan

To do this stretch:

1. Make a fist.
2. Stretch your fingers outwards as far as they can go, like a fan.
3. Repeat the movements 10 times.

12. Imaginary piano

To do this stretch:

1. Pretend to play a piano.
2. Flip your hands over and play an upside-down piano.

13. Finger pulls

To do this stretch:

1. Lay your hand flat on a table.
2. Gently pull a finger upward so that it points toward the ceiling.
3. Hold the position for 5 seconds.
4. Release the finger.
5. Repeat this on all the other fingers.

14. Alternate finger stretch

To do this stretch:

1. Bring the middle and ring fingers together.
2. Separate the pinky and index fingers from them.
3. Repeat the stretch 10 times.

15. Wrist-strengthener

To do this stretch:

1. Get into position on your hands and knees, with the fingers pointing toward the body.
2. Slowly lean forward, keeping your elbows straight.
3. Hold the position for 20 seconds.
4. Relax, then repeat the stretch.

Takeaway

Working with computers, writing, and doing manual labor put strain on the hands and wrists and can cause problems over time, such as tendonitis and carpal tunnel syndrome.

Taking frequent breaks and stretching before and while using the hands and wrists can help prevent strain. Improving flexibility and strength gradually can help people avoid wrist and hand injuries.

via Medical News Today: How to stretch your hands and wrists

[Abstract] Electromyogram-Related Neuromuscular Electrical Stimulation for Restoring Wrist and Hand Movement in Poststroke Hemiplegia: A Systematic Review and Meta-Analysis

Abstract

Background. Clinical trials have demonstrated some benefits of electromyogram-triggered/controlled neuromuscular electrical stimulation (EMG-NMES) on motor recovery of upper limb (UL) function in patients with stroke. However, EMG-NMES use in clinical practice is limited due to a lack of evidence supporting its effectiveness.

Objective. To perform a systematic review and meta-analysis to determine the effects of EMG-NMES on stroke UL recovery based on each of the International Classification of Functioning, Disability, and Health (ICF) domains.

Methods. Database searches identified clinical trials comparing the effect of EMG-NMES versus no treatment or another treatment on stroke upper extremity motor recovery. A meta-analysis was done for outcomes at each ICF domain (Body Structure and Function, Activity and Participation) at posttest (short-term) and follow-up periods. Subgroup analyses were conducted based on stroke chronicity (acute/subacute, chronic phases). Sensitivity analysis was done by removing studies rated as poor or fair quality (PEDro score <6).

Results. Twenty-six studies (782 patients) met the inclusion criteria. Fifty percent of them were considered to be of high quality. The meta-analysis showed that EMG-NMES has a robust short-term effect on improving UL motor impairment in the Body Structure and Function domain. No evidence was found in favor of EMG-NMES for the Activity and Participation domain. EMG-NMES had a stronger effect for each ICF domain in chronic (≥3 months) compared to acute/subacute phases.

Conclusion. EMG-NMES is effective in the short term in improving UL impairment in individuals with chronic stroke.

 

via Electromyogram-Related Neuromuscular Electrical Stimulation for Restoring Wrist and Hand Movement in Poststroke Hemiplegia: A Systematic Review and Meta-Analysis – Katia Monte-Silva, Daniele Piscitelli, Nahid Norouzi-Gheidari, Marc Aureli Pique Batalla, Philippe Archambault, Mindy F. Levin, 2019

[Webthesis] DESIGN AND CONTROL OF A ROBOTIC EXOSKELETON FOR WRIST REHABILITATION – Full Text

Abstract

Control of a exoskeleton with different sensors using a microcontroller and Matlab: This project will be used the exoskeleton for wrist rehabilitation and evaluation designed in the RoboticsLab. This device is actuated with SMA (Shape Memory Alloys) wires and it has two DOF. The objectives of the work will be: to integrate position and pressure sensors into the exoskeleton; to use the information of these sensors to control in position and / or strength the exoskeleton in repetitive tasks for the flexion-extension movement of the wrist; collect data on the execution of the task that could be used by the doctor to evaluate the patient’s progression.

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via DESIGN AND CONTROL OF A ROBOTIC EXOSKELETON FOR WRIST REHABILITATION – Webthesis