This project was supported by Chang Gung Medical Foundation with grant BMRP390021 and the Ministry of Science and Technology with grants MOST 107-2218-E-182A-001 and 108-2218-E-182A-001.

The training protocol and informed consent document were reviewed and approved by the Institutional Review Board of the Chang Gung Medical Foundation. The details of the study and the procedures were clearly explained to each subject.
1. Recruitment of three healthy adults
<ol>
	<li>Perform the screening process using the following inclusion criteria: (1) age 20&#8211;60 years, (2) already signed informed consent, (3) normal function in upper limbs, (4) Mini-Mental State Examination (MMSE) score &#8807;24.</li>
	<li>Conduct Trial 1: manipulating objects without wearing the robotic hand system.
	<ol>
		<li>Instruct the subject to sit upright in a chair with a firm back and no armrests. Seat the subject in front of a table. Stand by the subject&#8217;s non-dominant side.</li>
		<li>Teach the subject how to manipulate the designed objects for 5 min. Include a palmar prehension to pick up the peg, a lateral prehension to pick up the rectangular cube, a three-point chuck to pick up the cube, a spherical grasp to pick up the ball, and a cylindrical grasp to pick up the cylindrical bar. 
		NOTE: The objects are shown in Figure 1A. The experimental setup is shown in Figure 1B. The subjects learned the specific grasp patterns for each object. The grasping pattern is shown in Figure 2.</li>
		<li>Place two bases bilaterally in front of the subject&#8217;s hands. Place each object used in the rehabilitation on top of these bases to assist manipulation. For all the objects, repeat the following sequences 20 times. Ask the subjects to grasp the objects in the starting area of the base, lift, and move them to the midline and release using their non-dominant hands.</li>
		<li>At the same time, measure the success rate for these 20 attempts. Perform this procedure on 3 consecutive days. The success rate is the number of successful manipulations per 20 attempts x 100%. Successful manipulation is defined as when the subjects are able to complete the sequences with specific grasp pattern according to the objects and without dropping them.</li>
	</ol>
	</li>
	<li>Conduct Trial 2: manipulating objects using robotic hand system (Figure 3). 
	NOTE: The mechanisms of the robotic hand system are as follows. In the exoskeleton hand, the joints in each finger module are designed in mechanical linking and driven by an individual linear actuator with a constant speed of 10 mm/s. The exoskeleton has different ranges of motion in each finger module (thumb: MCP= 0&#176; to 55&#176;, DIP= 0&#176; to 70&#176;; index and middle fingers: MCP= -10 &#176; to 55&#176;, PIP=0&#176; to 35&#176;, DIP=0&#176; to 35&#176;; ring and little fingers: MCP= -5 &#176; to 55&#176;, PIP= 0&#176; to 35&#176;, DIP= 0&#176; to 35&#176;). In the sensor glove, each finger module is installed with a flex sensor which measures the joint angle and sends input signals to the control box through cables.
	<ol>
		<li>Sensor glove setup (Figure 1B,b)
		<ol>
			<li>Put the sensor glove&#160;on the subject&#8217;s dominant hand. Use the Velcro to secure the wrist.</li>
		</ol>
		</li>
		<li>Exoskeleton setup (Figure 1B,b)
		<ol>
			<li>Use a clean pad to wrap the non-dominant hand. Fasten the Velcro snugly.</li>
			<li>Loosen the thumb mechanism of the exoskeleton hand to allow adjustment of the thumb-opening angle. Place the non-dominant hand in the exoskeleton hand. Fasten the Velcro to the palm through the fastening ring. Fasten the fingers one by one, beginning with the forefinger and finishing with the thumb.</li>
			<li>Then, fasten the Velcro parallel to the wrist through the fastening ring. Adjust the thumb to a comfortable angle and then tighten the thumb mechanism.</li>
		</ol>
		</li>
		<li>Control box setup (Figure 1A,c)
		<ol>
			<li>Insert the cables for the exoskeleton&#160;hand and sensor glove into the sockets in the exoskeleton&#160;hand and sensor glove, respectively. After that, insert the cables for the exoskeleton&#160;hand and sensor glove into the socket in the control box. Finally, insert the power cable into the control box and connect it to an outlet with the correct voltage.</li>
		</ol>
		</li>
		<li>Conduct a warm-up session (The PROM mode)
		<ol>
			<li>Switch on the control box and adjust the mode to Five Fingers. This mode allows the exoskeleton hand to move the subject&#8217;s fingers passively. Ask the subject to perform a grasp-and-release task guided by the exoskeleton hand for 2.5 min.</li>
			<li>Switch the mode to Single Finger and let the exoskeleton&#160;hand move the subject&#8217;s fingers individually and passively. Ask the subject to extend and retract individual fingers for 2.5 min, guided by the exoskeleton&#160;hand.</li>
		</ol>
		</li>
		<li>Conduct a robot-assisted bimanual movement session.
		<ol>
			<li>Switch the mode to Mirror. In this mode, the movement of the dominant hand wearing the sensor glove controls the exoskeleton hand&#8217;s movements. Any movement that is made by the sensor glove is mimicked and mirrored by the exoskeleton&#160;hand. For example, a flexion of the sensor glove&#8217;s index finger corresponds to a flexion of the exoskeleton&#8217;s index finger.</li>
		</ol>
		</li>
		<li>Instruct the subject to perform a grasp-and-release task for 2.5 min and make individual finger movements for a further 2.5 min while wearing the sensor glove. This action is mirrored by the exoskeleton hand, which guides the subject&#8217;s non-dominant hand in performing the required tasks.</li>
	</ol>
	</li>
	<li>Conduct the task-oriented session.
	<ol>
		<li>Teach the subject how to manipulate the designed objects using the robotic hand system for 5 min. Include a palmar prehension to pick up the peg, a lateral prehension to pick up the rectangular cube, a three-point chuck to pick up the cube, a spherical grasp to pick up the ball, and a cylindrical grasp to pick up the cylindrical bar.</li>
		<li>Place two bases bilaterally in front of the subject&#8217;s hands. Place each object used in the rehabilitation on top of these bases to assist manipulation. For all the objects, repeat the following sequences 20 times. Ask the subjects to grasp the object in the starting area of the base, lift, and move them to the midline and release using the robotic hand system.</li>
		<li>At the same time, measure the success rate for these 20 attempts. Perform this procedure on 3 consecutive days. The success rate is the number of successful manipulations per 20 attempts x 100%. Successful manipulation is defined as when the subjects are able to complete the sequences with specific grasp pattern using the robotic hand system and without dropping them. 
		NOTE: The success rate will be used to assess the feasibility of the bimanual robotic hand system in healthy subjects.</li>
	</ol>
	</li>
</ol>
2. Recruit three stroke patients to determine the applicability of the training program
<ol>
	<li>Perform the screening process using the following inclusion criteria: (1) age 20&#8211;60 years; (2) signed informed consent; (3) diagnosed with unilateral stroke &#8807; 1 month (4) Modified Ashworth Scale (MAS) score &#8806;2; (5) Brunnstrom stage &#8806;2; (6) MMSE score &#8807;24.</li>
	<li>Conduct Trial 1: manipulating objects when not using robotic hand system (Figure 2).
	<ol>
		<li>Let the subject sit upright in a chair with a firm back and no armrests. Seat the subject in front of a table. Stand by the subject&#8217;s affected side. Place a sling under the subject&#8217;s elbow and exoskeleton hand to support his/her affected arm.</li>
		<li>Teach the subject how to manipulate the designed objects for 5 min. Include a palmar prehension to pick up the peg, a lateral prehension to pick up the rectangular cube, a three-point chuck to pick up the cube, a spherical grasp to pick up the ball, and a cylindrical grasp to pick up the cylindrical bar.</li>
		<li>Place two bases bilaterally in front of the subject&#8217;s hands. Place each object used in the rehabilitation on top of these bases to assist manipulation. Ask the subject to manipulate the five different objects using his/her affected hand 20 times. Support the subject in moving his/her upper arm if needed.</li>
		<li>At the same time, measure the success rate for these 20 attempts. Perform this procedure on 3 consecutive days.</li>
	</ol>
	</li>
	<li>Conduct Trial 2: manipulating objects using robotic hand system (Figure 3).
	<ol>
		<li>Fit the exoskeleton hand to the subject&#8217;s affected hand and the sensor glove to the unaffected hand. Repeat steps 1.3.1&#8211;1.3.3. Place a sling under the subject&#8217;s elbow and exoskeleton hand to support his/her affected arm.</li>
		<li>Conduct a warm-up session (The PROM mode).
		<ol>
			<li>Switch on the control box and adjust the mode to Five Fingers. Ask the subject to perform a grasp-and-release task guided by the exoskeleton hand for 2.5 min.</li>
			<li>Switch the mode to Single Finger. Ask the subject to extend and retract individual fingers for 2.5 min, guided by the exoskeleton hand.</li>
			<li>Switch the mode to Mirror. Instruct the subject to perform a grasp-and-release task for 2.5 min and make individual finger movements for a further 2.5 min while wearing the sensor glove. This action is mirrored by the exoskeleton hand, which guides the subject&#8217;s affected hand in performing the required tasks.</li>
		</ol>
		</li>
		<li>Conduct a task-oriented session.</li>
		<li>Teach the subject how to manipulate the designed objects using the robotic hand system for 5 min. Include a palmar prehension to pick up the peg, a lateral prehension to pick up the rectangular cube, a three-point chuck to pick up the cube, a spherical grasp to pick up the ball, and a cylindrical grasp to pick up the cylindrical bar.</li>
		<li>Place two bases bilaterally in front of the subject&#8217;s hands. Place each object used in the rehabilitation on top of these bases to assist manipulation. For all the objects, repeat the following sequences 20 times. Ask the subjects to grasp the objects in the starting area of the base, lift, and move them to the midline and release using the robotic hand system.</li>
		<li>At the same time, measure the success rate for these 20 attempts. Perform this procedure on 3 consecutive days. The success rate is the number of successful manipulations per 20 attempts x 100%. Successful manipulation is defined as when the subjects are able to complete the sequences with specific grasp pattern using the robotic hand system and without dropping them. 
		NOTE: The success rate will be used to assess the feasibility of the robotic hand system in stroke patients.</li>
	</ol>
	</li>
</ol>
3. Patient evaluation
<ol>
	<li>To assess acceptability, ask the subjects following questions at the end of each session: (1) was the robotic hand system helpful for you to manipulate the objects? (2) were there any adverse events happened during or after the training program?</li>
</ol>

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	<li>Hung, C. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+effects+of+combination+of+robot-assisted+therapy+with+task-specific+or+impairment-oriented+training+on+motor+function+and+quality+of+life+in+chronic+stroke.">The effects of combination of robot-assisted therapy with task-specific or impairment-oriented training on motor function and quality of life in chronic stroke.</a> PM &amp; R: The Journal of Injury, Function, and Rehabilitation. 8 (8), 721-729 (2016).</li><li>SangWook, L., Landers, K. A., Hyung-Soon, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+a+biomimetic+hand+exotendon+device+(BiomHED)+for+restoration+of+functional+hand+movement+post-stroke.">Development of a biomimetic hand exotendon device (BiomHED) for restoration of functional hand movement post-stroke.</a> IEEE Transactions on Neural Systems and Rehabilitation Engineering. 22 (4), 886-898 (2014).</li><li>Johnson, M. J., Wisneski, K. J., Anderson, J., Nathan, D., Smith, R. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+of+ADLER:+The+Activities+of+Daily+Living+Exercise+Robot.">Development of ADLER: The Activities of Daily Living Exercise Robot.</a> Proceedings of IEEE/RAS-EMBS International Conference. , (2006).</li><li>Pignolo, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Robotics+in+neuro-rehabilitation.">Robotics in neuro-rehabilitation.</a> Journal of Rehabilitation Medicine. 41 (12), 955-960 (2009).</li><li>Timmermans, A. A., Spooren, A. I., Kingma, H., Seelen, H. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Influence+of+task-oriented+training+content+on+skilled+arm-hand+performance+in+stroke:+a+systematic+review.">Influence of task-oriented training content on skilled arm-hand performance in stroke: a systematic review.</a> Neurorehabilitation and Neural Repair. 24 (9), 858-870 (2010).</li><li>Schweighofer, N., Choi, Y., Winstein, C., Gordon, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Task-oriented+rehabilitation+robotics.">Task-oriented rehabilitation robotics.</a> American Journal of Physical Medicine &amp; Rehabilitation. 91, 270-279 (2012).</li><li>Almhdawi, K. A., Mathiowetz, V. G., White, M., delMas, R. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficacy+of+occupational+therapy+task-oriented+approach+in+upper+extremity+post-stroke+rehabilitation.">Efficacy of occupational therapy task-oriented approach in upper extremity post-stroke rehabilitation.</a> Occupational Therapy International. 23 (4), 444-456 (2016).</li><li>Takahashi, C. D., Der-Yeghiaian, L., Le, V. H., Cramer, S. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+robotic+device+for+hand+motor+therapy+after+stroke.">A robotic device for hand motor therapy after stroke.</a> Proceedings of 9th International Conference on Rehabilitation Robotics. , (2005).</li><li>Villafa&#241;e, J. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Efficacy+of+short-term+robot-assisted+rehabilitation+in+patients+with+hand+paralysis+after+stroke:+a+randomized+clinical+trial.">Efficacy of short-term robot-assisted rehabilitation in patients with hand paralysis after stroke: a randomized clinical trial.</a> Hand (NY). 13 (1), 95-102 (2018).</li><li>Cauraugh, J. H., Lodha, N., Naik, S. K., Summers, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bilateral+movement+training+and+stroke+motor+recovery+progress:+a+structured+review+and+meta-analysis.">Bilateral movement training and stroke motor recovery progress: a structured review and meta-analysis.</a> Human Movement Science. 29 (5), 853-870 (2010).</li><li>Brunner, I. C., Skouen, J. S., Strand, L. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Is+modified+constraint-induced+movement+therapy+more+effective+than+bimanual+training+in+improving+arm+motor+function+in+the+subacute+phase+post+stroke?+A+randomized+controlled+trial.">Is modified constraint-induced movement therapy more effective than bimanual training in improving arm motor function in the subacute phase post stroke? A randomized controlled trial.</a> Clinical Rehabilitation. 26 (12), 1078-1086 (2012).</li><li>Sleimen-Malkoun, R., Temprado, J. J., Thefenne, L., Berton, E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Bimanual+training+in+stroke:+how+do+coupling+and+symmetry-breaking+matter.">Bimanual training in stroke: how do coupling and symmetry-breaking matter.</a> BMC Neurology. 11, 11 (2011).</li><li>Yue, Z., Zhang, X., Wang, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hand+rehabilitation+robotics+on+poststroke+motor+recovery.">Hand rehabilitation robotics on poststroke motor recovery.</a> Behavioural Neurology. 2017, 1-20 (2017).</li><li>Dovat, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=HandCARE:+a+cable-actuated+rehabilitation+system+to+train+hand+function+after+stroke.">HandCARE: a cable-actuated rehabilitation system to train hand function after stroke.</a> IEEE Transactions on Neural Systems and Rehabilitation Engineering. 16 (6), 582-591 (2008).</li><li>Yoo, C., Park, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impact+of+task-oriented+training+on+hand+function+and+activities+of+daily+living+after+stroke.">Impact of task-oriented training on hand function and activities of daily living after stroke.</a> Journal of Physical Therapy Science. 27 (8), 2529-2531 (2015).</li></ol>

The authors declare no conflict of interest.

The results of this study showed the following: (1) both groups could successfully grasp the objects provided with the robotic hand system. They were able to complete this task with a nearly 100% success rate, which verifies the feasibility of the proposed robot-assisted task-oriented training program. (2) There were no reports of injury or adverse events during the study period and all patients reported that the robotic hand system was helpful to manipulate objects. This confirmed the acceptability of the robotic hand s...

Most (80%) stroke patients experience a deficit in the hand and have difficulty in independently performing manual tasks that are pertinent to daily living1. However, the complex nature of manual tasks means that it is a significant challenge to design a task-oriented training program for hand rehabilitation2. In recent years, many robotic devices have been developed for hand rehabilitation3,4, but few training protocols assisted by robotic devices allow a patient to interact with real objects. It is unclear exactly how a task-oriented training program for hand function rehabilitation can be applied using robotic devices for patients who experience hand dysfunction due to stroke.
Task-oriented training is used to improve hand function5,6 and is commonly applied in the rehabilitation for upper limb dysfunction due to stroke. It is used to increase neuroplasticity and is highly dependent on individual neurological deficits and functional demands7. However, during task-oriented training, patients experience difficultly in manipulating objects if hand function is impaired. Examples of this include poor grasp or limited pinch functions. Therapists also show difficulty in guiding patients&#8217; finger movements individually, which therefore limits the variation of grasping tasks. Robotic devices are thus necessary to increase the effectiveness of task-oriented training by explicitly guiding hand movement during repetitive training2,8.
Previous studies only used rehabilitation robots for task-oriented training on upper-limb reaching tasks3. It is unclear how robot-assisted rehabilitation can be employed for task-oriented training targeting at hand function. An exoskeleton&#160;hand, HWARD, has been used to guide the fingers to grasp and release objects8. However, this device does not allow varied grasping patterns because it lacks the necessary degrees of freedom. Recently, other devices that target moving a patient&#8217;s fingers individually have been developed9. However, these devices have not previously been used for neurorehabilitation. The robotic devices mentioned above are all unilateral robots. In contrast, the robotic hand system presented here needs the cooperation of unaffected and affected hands. The robotic hand system is specifically designed for rehabilitation purposes using the master&#8211;slave mechanism to achieve symmetric bimanual hand movements. The system consists of an exoskeleton hand (worn on the affected hand), a control box, and a sensory glove (worn on the unaffected hand). Each finger module of the exoskeleton hand is driven by a motor with one degree of freedom and its joints are linked using a mechanical linkage system. Two sizes, S and M, are designed to fit different subjects. The control box provides two therapeutic modes, the passive range of motion (PROM) and mirror-guided motion modes, through which the patient&#8217;s affected hand can be manipulated by the exoskeleton hand. In the PROM mode, the control box sends input commands to the exoskeleton while moves the subject&#8217;s hand to perform full finger flexion/extension. It contains two modes: single-finger mode (acts in sequence from thumb to little finger) and five fingers mode (five fingers move together). In the mirror-guided motion mode, the master (sensor glove)&#8211;slave (exoskeleton hand) mechanism is implemented, in which the movement of each finger is detected by the sensor glove and signals of the joint angles are transmitted to the control box to manipulate the exoskeleton hand.
When equipped the robotic hand system, the subjects were instructed to move their affected hands under the guidance of the exoskeleton hand controlled by unaffected hands which is bimanual movement training (BMT)10. According to previous research, BMT is able to activate similar neural pathways in both hemispheres of the brain and prevent the trans-hemisphere inhibition that hinders the recovery of neuronal function in the lesion hemisphere10. Brunner et al.11 compared BMT to constraint-induced movement therapy (CIMT) in sub-acute stroke patients. They suggested that BMT tends to activate more neural networks in both hemispheres than CIMT, and there was no significant difference in improvement of hand function between the BMT and CIMT approaches. Sleimen-Malkoun et al.12 also suggested that through BMT, stroke patients are able to re-establish both paretic limb control and bimanual control. That is to say, training should comprise bimanual tasks that focus on using the affected arm. Moreover, the coordination of both hands is necessary for activities of daily living (ADL)11,12. Therefore, it is crucial to develop a bimanual robot-assisted task-oriented training program for post-stroke patients and objects that can be grasped or pinched by patients wearing the robotic hand system.
In this study, a variety of grasping objects were designed based on the needs of occupational therapy and the mechanical properties of rehabilitation robots. A task-oriented training protocol was developed using robotic rehabilitation devices for patients with distal upper limb dysfunction due to stroke. The purpose of this study was to investigate the feasibility, and acceptability of the task-oriented training program using an exoskeleton robot and newly designed grasping objects.

<table><tbody><tr><td>Control Box</td><td>Rehabotics Medical Technology Corporation</td><td>HB01</td><td>The control box includes a power supply, sensor glove signal receiver, motor signal transmitter, and exoskeletal hand motion mode selection unit.</td></tr><tr><td>Exoskeletal Hand</td><td>Rehabotics Medical Technology Corporation</td><td>HS01</td><td>It is a wearable device causing the patient&#039;s fingers to move and is driven by an external motor and mechanical assembly.</td></tr><tr><td>Sensor Glove</td><td>Rehabotics Medical Technology Corporation</td><td>HM01</td><td>Worn on the patient&#039;s unaffected side hand. The sensors in the sensor glove will detect flexing and extension of the hand, and this data will be used to control the exoskeletal hand when in bimanual mode.</td></tr></tbody></table>

development of a novel task-oriented rehabilitation program using a bimanual exoskeleton robotic hand

A robot-assisted hand is used for the rehabilitation of patients with impaired upper limb function, particularly for stroke patients with a loss of motor control. However, it is unclear how conventional occupational training strategies can be applied to the use of rehabilitation robots. Novel robotic technologies and occupational therapy concepts are used to develop a protocol that allows patients with impaired upper limb function to grasp objects using their affected hand through a variety of pinching and grasping functions. To conduct this appropriately, we used five types of objects: a peg, a rectangular cube, a cube, a ball, and a cylindrical bar. We also equipped the patients with a robotic hand, the Mirror Hand, an exoskeleton&#160;hand that is fitted to the subject&#8217;s affected hand and follows the movement of the sensor glove fitted to their unaffected hand (bimanual movement training (BMT)). This study had two stages. Three healthy subjects were first recruited to test the feasibility and acceptability of the training program. Three patients with hand dysfunction caused by stroke were then recruited to confirm the feasibility and acceptability of the training program, which was conducted on 3 consecutive days. On each day, the patient was monitored during 5 min of movement in a passive range of motion, 5 min of robot-assisted bimanual movement, and task-oriented training using the five objects. The results showed that both healthy subjects and subjects who had suffered a stroke in conjunction with the robotic hand could successfully grasp the objects. Both healthy subjects and those who had suffered a stroke performed well with the robot-assisted task-oriented training program in terms of feasibility and acceptability.

A total of six subjects were enrolled in this study, including three healthy subjects and three post-stroke subjects. The demographic data of both groups are shown in Supplementary Table 1. The average age of the healthy group was 28 (range: 24&#8211;30), whereas the average age of the patient group was 49 (40&#8211;57). The average assessment scores of the patient group were as follows: (1) MMSE=27 (26&#8211;29), (2) FMA=11.3 (6&#8211;15), (3) MAS=1, (4) Brunnstrom stage=2.
I...

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Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand

This study reports the development of a novel robot-assisted task-oriented program for hand rehabilitation. The developmental process consists of experiments using both healthy subjects and subjects who have had a stroke and suffered from subsequent motor control dysfunction.

A robot-assisted hand is used for the rehabilitation of patients with impaired upper limb function, particularly for stroke patients with a loss of motor ...

development-novel-task-oriented-rehabilitation-program-using-bimanual

Research

JoVE Journal

Medicine

6.9K Views.  Chang Gung Memorial Hospital at Taoyuan. This study reports the development of a novel robot-assisted task-oriented program for hand rehabilitation. The developmental process consists of experiments using both healthy subjects and subjects who have had a stroke and suffered from subsequent motor control dysfunction.

Video: Development of a Novel Task-oriented Rehabilitation Program using a Bimanual Exoskeleton Robotic Hand

A Novel Capsulorhexis Technique Using Shearing Forces with Cystotome

Purpose:
To demonstrate a capsulorhexis technique using predominantly shearing forces with a cystotome on a virtual reality simulator and on a human eye.
Method:
Our technique involves creating the initial anterior capsular tear with a cystotome to raise a flap. The flap left unfolded on the lens surface. The cystotome tip is tilted horizontally and is engaged on the flap near the leading edge of the tear. The cystotome is moved in a circular fashion to direct the vector forces. The loose flap is constantly swept towards the centre so that it does not obscure the view on the tearing edge.
Results:
Our technique has the advantage of reducing corneal wound distortion and subsequent anterior chamber collapse. The capsulorhexis flap is moved away from the tear leading edge allowing better visualisation of the direction of tear. This technique offers superior control of the capsulorhexis by allowing the surgeon to change the direction of the tear to achieve the desired capsulorhexis size.
Conclusions:
The EYESI Surgical Simulator is a realistic training platform for surgeons to practice complex capsulorhexis techniques. The shearing forces technique is a suitable alternative and in some cases a far better technique in achieving the desired capsulorhexis.

This video demonstrates a novel capsulorhexis technique in modern cataract surgery. Capsulorhexis is the most difficult and important part of phacoemulsification surgery.

Purpose:
To demonstrate a capsulorhexis technique using predominantly shearing forces with a cystotome on a virtual reality simulator and on a human eye....

Haptic/Graphic Rehabilitation: Integrating a Robot into a Virtual Environment Library and Applying it to Stroke Therapy

Recent research that tests interactive devices for prolonged therapy practice has revealed new prospects for robotics combined with graphical and other forms of biofeedback. Previous human-robot interactive systems have required different software commands to be implemented for each robot leading to unnecessary developmental overhead time each time a new system becomes available. For example, when a haptic/graphic virtual reality environment has been coded for one specific robot to provide haptic feedback, that specific robot would not be able to be traded for another robot without recoding the program. However, recent efforts in the open source community have proposed a wrapper class approach that can elicit nearly identical responses regardless of the robot used. The result can lead researchers across the globe to perform similar experiments using shared code. Therefore modular "switching out"of one robot for another would not affect development time. In this paper, we outline the successful creation and implementation of a wrapper class for one robot into the open-source H3DAPI, which integrates the software commands most commonly used by all robots.

Recently, a vast amount of prospects have come available for human-robot interactive systems. In this paper we outline the integration of a new robotic device with open source software that can rapidly make possible a library of interactive functionality. We then outline a clinical application for a neurorehabilitation application.

Recent research that tests interactive devices for prolonged therapy practice has revealed new prospects for robotics combined with graphical and other ...

Bioengineering

A Structured Rehabilitation Protocol for Improved Multifunctional Prosthetic Control: A Case Study

Advances in robotic systems have resulted in prostheses for the upper limb that can produce multifunctional movements. However, these sophisticated systems require upper limb amputees to learn complex control schemes. Humans have the ability to learn new movements through imitation and other learning strategies. This protocol describes a structured rehabilitation method, which includes imitation, repetition, and reinforcement learning, and aims to assess if this method can improve multifunctional prosthetic control. A left below elbow amputee, with 4 years of experience in prosthetic use, took part in this case study. The prosthesis used was a Michelangelo hand with wrist rotation, and the added features of wrist flexion and extension, which allowed more combinations of hand movements. The participant&#8217;s Southampton Hand Assessment Procedure score improved from 58 to 71 following structured training. This suggests that a structured training protocol of imitation, repetition and reinforcement may have a role in learning to control a new prosthetic hand. A larger clinical study is however required to support these findings.

As prosthetic development moves towards the goal of natural control, harnessing amputees&#8217; inherent ability to learn new motor skills may enable proficiency. This manuscript describes a structured rehabilitation protocol, which includes imitation, repetition, and reinforcement learning strategies, for improved multifunctional prosthetic control.

Advances in robotic systems have resulted in prostheses for the upper limb that can produce multifunctional movements. However, these sophisticated ...

Behavior

Robotic Mirror Therapy System for Functional Recovery of Hemiplegic Arms

Mirror therapy has been performed as effective occupational therapy in a clinical setting for functional recovery of a hemiplegic arm after stroke. It is conducted by eliciting an illusion through use of a mirror as if the hemiplegic arm is moving in real-time while moving the healthy arm. It can facilitate brain neuroplasticity through activation of the sensorimotor cortex. However, conventional mirror therapy has a critical limitation in that the hemiplegic arm is not actually moving. Thus, we developed a real-time 2-axis mirror robot system as a simple add-on module for conventional mirror therapy using a closed feedback mechanism, which enables real-time movement of the hemiplegic arm. We used 3 Attitude and Heading Reference System sensors, 2 brushless DC motors for elbow and wrist joints, and exoskeletal frames. In a feasibility study on 6 healthy subjects, robotic mirror therapy was safe and feasible. We further selected tasks useful for activities of daily living training through feedback from rehabilitation doctors. A chronic stroke patient showed improvement in the Fugl-Meyer assessment scale and elbow flexor spasticity after a 2-week application of the mirror robot system. Robotic mirror therapy may enhance proprioceptive input to the sensory cortex, which is considered to be important in neuroplasticity and functional recovery of hemiplegic arms. The mirror robot system presented herein can be easily developed and utilized effectively to advance occupational therapy.

We developed a real-time mirror robot system for functional recovery of hemiplegic arms using automatic control technology, conducted a clinical study on healthy subjects, and determined tasks through feedback from rehabilitation doctors. This simple mirror robot can be applied effectively to occupational therapy in stroke patients with a hemiplegic arm.

Mirror therapy has been performed as effective occupational therapy in a clinical setting for functional recovery of a hemiplegic arm after stroke. It is ...

Revolutionizing Stroke Rehabilitation with Enhanced Grasping and Finger Recovery

A Flexible Wearable Supernumerary Robotic Limb for Chronic Stroke Patients

In this study, we present a flexible wearable supernumerary robotic limb that helps chronic stroke patients with finger rehabilitation and grasping movements. The design of this innovative limb draws inspiration from bending pneumatic muscles and the unique characteristics of an elephant's trunk tip. It places a strong emphasis on crucial factors such as lightweight construction, safety, compliance, waterproofing, and achieving a high output-to-weight/pressure ratio. The proposed structure enables the robotic limb to perform both envelope and fingertip grasping. Human-robot interaction is facilitated through a flexible bending sensor, detecting the wearer's finger movements and connecting them to motion control via a threshold segmentation method. Additionally, the system is portable for versatile daily use. To validate the effectiveness of this innovation, real-world experiments involving six chronic stroke patients and three healthy volunteers were conducted. The feedback received through questionnaires indicates that the designed mechanism holds immense promise in assisting chronic stroke patients with their daily grasping activities, potentially improving their quality of life and rehabilitation outcomes.

Author Spotlight: Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs 

This protocol introduces a flexible wearable supernumerary robotic limb tailored to assist in finger rehabilitation for stroke patients. The design incorporates a bending sensor to facilitate seamless human-robot interaction. Validation through experiments involving both healthy volunteers and stroke patients underscores the efficacy and dependability of the proposed study.

In this study, we present a flexible wearable supernumerary robotic limb that helps chronic stroke patients with finger rehabilitation and grasping ...

Engineering

Functional MRI in Conjunction with a Novel MRI-compatible Hand-induced Robotic Device to Evaluate Rehabilitation of Individuals Recovering from Hand Grip Deficits

Functional magnetic resonance imaging (fMRI) is a non-invasive magnetic resonance imaging technique that images brain activation in vivo, using endogenous deoxyhemoglobin as an endogenous contrast agent to detect changes in blood-level-dependent oxygenation (BOLD effect). We combined fMRI with a novel robotic device (MR-compatible hand-induced robotic device [MR_CHIROD]) so that a person in the scanner can execute a controlled motor task, hand-squeezing, which is a very important hand movement to study in neurological motor disease. We employed parallel imaging (generalized auto-calibrating partially parallel acquisitions [GRAPPA]), which allowed higher spatial resolution resulting in increased sensitivity to BOLD. The combination of fMRI with the hand-induced robotic device allowed precise control and monitoring of the task that was executed while a participant was in the scanner; this may prove to be of utility in rehabilitation of hand motor function in patients recovering from neurological deficits (e.g., stroke). Here we outline the protocol for using the current prototype of the MR_CHIROD during an fMRI scan.

We performed functional MRI using a novel MRI-compatible hand-induced robotic device to evaluate its utility for monitoring hand motor function in individuals recovering from neurological deficits.

Functional magnetic resonance imaging (fMRI) is a non-invasive magnetic resonance imaging technique that images brain activation in vivo, using endogenous ...

Neuroscience

Surface Electromyographic Biofeedback as a Rehabilitation Tool for Patients with Global Brachial Plexus Injury Receiving Bionic Reconstruction

In patients with global brachial plexus injury and lack of biological treatment alternatives, bionic reconstruction, including the elective amputation of the functionless hand and its replacement with a prosthesis, has recently been described. Optimal prosthetic function depends on a structured rehabilitation protocol, as residual muscle activity in a patient&#8217;s arm is later translated into prosthetic function. Surface electromyographic (sEMG) biofeedback has been used during rehabilitation after stroke, but has so far not been used in patients with complex peripheral nerve injuries. Here, we present our rehabilitation protocol implemented in patients with global brachial plexus injuries suitable for bionic reconstruction, starting from identification of sEMG signals to final prosthetic training. This structured rehabilitation program facilitates motor relearning, which may be a cognitively debilitating process after complex nerve root avulsion injuries, aberrant re-innervation and extra-anatomical reconstruction (as is the case with nerve transfer surgery). The rehabilitation protocol using sEMG biofeedback aids in the establishment of new motor patterns as patients are being made aware of the advancing re-innervation process of target muscles. Additionally, faint signals may also be trained and improved using sEMG biofeedback, rendering a clinically &#34;useless&#34;&#160;muscle (exhibiting muscle strength M1 on the British Medical Research Council [BMRC] scale) eligible for dexterous prosthetic hand control. Furthermore, functional outcome scores after successful bionic reconstruction are presented in this article.

Optimal functional outcomes after bionic reconstruction in patients with global brachial plexus injury depend on a structured rehabilitation protocol. Surface electromyographic guided training may improve the amplitude, separation and consistency of EMG signals, which - after elective amputation of a functionless hand - control and drive a prosthetic hand.

In patients with global brachial plexus injury and lack of biological treatment alternatives, bionic reconstruction, including the elective amputation of ...

Brain-Computer Interface-controlled Upper Limb Robotic System for Enhancing Daily Activities in Stroke Patients

This study introduces a Brain-Computer Interface (BCI)-controlled upper limb assistive robot for post-stroke rehabilitation. The system utilizes electroencephalogram (EEG) and electrooculogram (EOG) signals to help users assist upper limb function in everyday tasks while interacting with a robotic hand. We evaluated the effectiveness of this BCI-robot system using the Berlin Bimanual Test for Stroke (BeBiTS), a set of 10 daily living tasks involving both hands. Eight stroke patients participated in this study, but only four participants could adapt to the BCI robot system training and perform the postBeBiTS. Notably, when the preBeBiTS score for each item was four or less, the BCI robot system showed greater assistive effectiveness in the postBeBiTS assessment. Furthermore, our current robotic hand does not assist with arm and wrist functions, limiting its use in tasks requiring complex hand movements. More participants are required to confirm the training effectiveness of the BCI-robot system, and future research should consider using robots that can assist with a broader range of upper limb functions. This study aimed to determine the BCI-robot system's ability to assist patients in performing daily living activities.

This study introduces a brain-computer interface (BCI) system for stroke patients, which combines electroencephalography and electrooculography signals to control an upper limb robotic hand, enhancing daily activities. The evaluation used the Berlin Bimanual Test for Stroke (BeBiTS).

This study introduces a Brain-Computer Interface (BCI)-controlled upper limb assistive robot for post-stroke rehabilitation. The system utilizes ...

Integrated Robotic and Conventional Therapy for Post-Stroke Upper Limb Recovery

Enhancing Upper Limb Function and Motor Skills Post-Stroke Through an Upper Limb Rehabilitation Robot

Cerebrovascular accidents, commonly known as strokes, represent a prevalent neurological event leading to significant upper limb disabilities, thereby profoundly affecting individuals' activities of daily living and diminishing their quality of life. Traditional rehabilitation methods for upper limb recovery post-stroke are often hindered by limitations, including therapist and patient fatigue, reliance on singular training methodologies, and lack of sustained motivation. Addressing these challenges, this study introduces an upper limb rehabilitation robot, which uses intelligent feedback motion control to improve therapeutic outcomes. The system is distinguished by its capability to adjust the direction and magnitude of force feedback dynamically, based on the detection of spastic movements during exercises, thereby offering a tailored therapeutic experience. This system is equipped with four distinct training modes, intelligent assessment of joint range of motion, and the ability to personalize training programs. Moreover, it provides an immersive interactive gaming experience coupled with comprehensive safety measures. This multifaceted approach not only elevates the engagement and interest of participants beyond traditional rehabilitation protocols but also demonstrates significant improvements in upper limb functionality and the activities of daily living among hemiplegic patients. The system exemplifies an advanced tool in upper limb rehabilitation, offering a synergistic blend of precision, personalization, and interactive engagement, thereby broadening the therapeutic options available to stroke survivors.

Author Spotlight: Enhancing Post-Stroke Upper Limb Rehabilitation with Robotic Technologies for Improved Motor Recovery and Functional Outcomes

This protocol describes an upper limb rehabilitation robot that provides intelligent feedback through four modes. These modes enhance upper limb function and flexibility, thereby improving patients' quality of life.

Cerebrovascular accidents, commonly known as strokes, represent a prevalent neurological event leading to significant upper limb disabilities, thereby ...

Dual Upper Limb Robotic Training in Stroke Rehabilitation

Application of a Dual Upper Limb Task-Oriented Robotic System for the Functional Recovery of the Upper Limb in Stroke Patients

Highly repetitive and task-oriented training has been shown to promote the recovery of limb function in stroke patients. Additionally, bilateral arm training can help stroke survivors regain their upper limb function and improve their daily activities. The dual upper limb task-oriented robotic system is designed to assist the healthy side of the stroke patient in driving the affected side to perform bilateral arm training through the use of a robotic device. It can also guide the patient in carrying out dual upper limb coordinated movements and engage them in a task-oriented virtual game using force feedback and human-computer interaction technology. This study aimed to assess the efficacy of the system in enhancing upper limb function and activities of daily living in stroke patients. The assessment methods used included motor evoked potential (MEP), functional test for the hemiplegic upper extremity-Hong Kong (FTHUE-HK), Fugl-Meyer Assessment Upper Extremity Scale (FMA-UE), and modified Barthel index (MBI). The results of the study indicate that the dual upper limb task-oriented robotic system can significantly improve the corticospinal pathway, upper limb function, and activities of daily living in stroke patients after 6 weeks of treatment. This system can serve as an effective adjunct to upper limb functional rehabilitation in stroke survivors, reducing the dependence on rehabilitation therapists. In conclusion, the dual upper limb task-oriented robotic system provides a new strategy for post-stroke limb functional rehabilitation and holds great potential for application, as it offers certain social and financial benefits.

Author Spotlight: Enhancing Upper Limb Rehabilitation in Stroke Patients Through Advanced Robotic and Neuromodulation Technologies

This experimental protocol outlines the use of a dual upper limb task-oriented robotic system for stroke patients with upper limb dysfunction. The findings indicate that this system can significantly improve stroke patients' upper limb function and daily living activities.

Highly repetitive and task-oriented training has been shown to promote the recovery of limb function in stroke patients. Additionally, bilateral arm ...