The authors wish to appreciate Christopher Neville, Girolamo Mammolito, and F. Jerome Pabulayan for their vital contributions to developing this protocol and data collection.

The Institutional Review Board (IRB) of SUNY Upstate Medical University approved this protocol.
1. Participant screening
<ol>
	<li>Perform all research methods with IRB approval by the Declaration of Helsinki.</li>
	<li>Recruit non-disabled adults who do not have any neurological or musculoskeletal issues that prevent upper extremity motor task performance.</li>
	<li>Recruit chronic stroke survivors whose stroke onset is at least six months before study participation and who have mild-to-moderate upper extremity motor impairment, indicated by Fugl-Meyer Assessment of upper extremity score of 19 to 60 out of 66, and can extend hemiparetic wrist and fingers at least 10 degrees voluntarily.</li>
	<li>Schedule potential participants to attend a data collection session.</li>
	<li>Obtain written informed consent from all research participants before initiating any experimental procedures.</li>
	<li>Screen all participants for study participation eligibility using questionnaires regarding their demographics, previous arm injury history, hand dominance, and confidence in specific fine hand motor skill tasks.</li>
</ol>
2. Upper Extremity Motor Outcome Measures
<ol>
	<li>Perform the Perdue Pegboard Test with the standard procedure10.</li>
	<li>Perform the Fugl-Meyer Assessment of Upper Extremity Motor (FMA-UE) using the standard procedure11,12.</li>
</ol>
3. Psychosocial and cognitive-behavioral assessments
<ol>
	<li>Have participants complete the following questionnaires using the online survey platform: Edinburg Handedness Inventory; a questionnaire for previous experience on the use of chopsticks.; and a self-efficacy questionnaire for the use of chopsticks.</li>
</ol>
4. Preparation of Goal-directed Arm Reaching Tasks
<ol>
	<li>Prepare the motion capture camera system for kinematic recording.
	<ol>
		<li>Calibrate the motion capture camera using the motion capture workstation software.</li>
		<li>Set the origin of the world coordinate using the motion capture workstation software.</li>
		<li>Place all marker triads on a table in the field of view of motion capture cameras and check if all marker triads are within the field of view.</li>
	</ol>
	</li>
	<li>Prepare the motion capture data acquisition software to build the skeletal model.
	<ol>
		<li>Import the marker sets from the motion capture workstation software to the motion capture data acquisition software.</li>
		<li>Activate virtual sensors (i.e., marker triads).</li>
		<li>Set world axes.</li>
		<li>Assign virtual sensors to body segments of the skeleton model.</li>
	</ol>
	</li>
	<li>Set up goal-directed arm reaching task conditions.
	<ol>
		<li>Place a table at the center of the motion capture cameras field of view.</li>
		<li>Put the laminated goal-directed arm reaching template paper at the designated area on the table.</li>
		<li>Prepare a pair of chopsticks on the table.</li>
		<li>Prepare to play the auditory cue audio file.</li>
		<li>Prepare the task instruction scripts.</li>
		<li>Test the motion capture system to ensure it is working appropriately.</li>
	</ol>
	</li>
	<li>Set up the participant.
	<ol>
		<li>Attach the reflective marker triads to the skin of the participant&#39;s arms, hands, and trunk. Use the following description for the marker triad locations: 
		A marker triad for the trunk: between medial borders of the scapulae 
		A marker triad for each upper arm: in the middle of the lateral surface of the upper arm 
		A marker triad for each forearm: in the middle of the dorsal surface of the forearm 
		&#8203;A marker triad for each hand: in the middle of the dorsal surface of the 3rd metacarpal bone</li>
		<li>Prepare a chopstick with a marker triad.</li>
		<li>Place a marker triad on a table located center of the field of view of motion capture cameras.</li>
		<li>Digitize the participant&#39;s body segments using an upper extremity joints and trunk skeleton model that includes following landmarks using the motion capture data acquisition software: 
		Upper trunk: a spot between C7 and T1 vertebrae 
		Lower trunk: a spot between T12 and L1 vertebrae 
		Shoulder (glenohumeral joint), two spots equidistance from center of the head of humerus 
		Elbow: two spots on the medial and lateral elbow that are equidistant from the joint center 
		Wrist: two spots on the medial and lateral wrist that are equidistant from the joint center 
		&#8203;Hand: the tip of the third phalanx of each hand</li>
		<li>Digitize the tip of the chopstick with a marker triad using the motion capture data acquisition software.</li>
		<li>Digitize the home position and target position using the marker triad located on the table using the motion capture data acquisition software.</li>
	</ol>
	</li>
</ol>
5. Performance of Goal-directed Arm Reaching Tasks
<ol>
	<li>Position the participant in a sitting position.</li>
	<li>Ask the participant to reach forward without trunk movement, then locate the table to position the target at approximately 80% of the participant&#39;s maximum arm reaching distance.</li>
	<li>Instruct the participant to maintain the upright trunk posture at the beginning of each task performance. There will be no restriction to the trunk movements during the task performance.</li>
	<li>Instruct the participant how to use chopsticks using a Youtube video (https://youtu.be/2Bns2m5Bg4M) to standardize the way to use the chopsticks.</li>
	<li>Perform the task condition 1 - Reaching and Pointing to a large target.
	<ol>
		<li>Instruct the participant to hold a chopstick with the dominant hand (non-disabled adults) or the paretic hand (stroke participants). The participant will place the tip of a chopstick touching at the center of the home position. Instruct the participant to maintain the upright trunk posture at the beginning.</li>
		<li>Fixate the task condition template paper at the designated area on the table. The template paper includes two squares with a cross at the center of each square: one for the home position and the other one for the target area. For this task, the target square size is 1 x 1 cm2. The target position is located 20 in front of the home position.</li>
		<li>Describe the task instructions.
		<ol>
			<li>State the following: &#34;The goal of this task is to reach and tap the target area with the chopstick&#39;s tip as quickly and accurately as possible. You will hold a chopstick with your right (or left) [indicate the performing hand]. Place the chopstick&#39;s tip on the home position [indicate the home position]. When you hear a &#39;GO&#39; signal, reach and tap the target [indicate the target] with the chopstick&#39;s tip as quickly as possible. Try to tap the center of the target as much as you can. You will have three seconds to tap the target. I will give you a &#39;STOP&#39; signal 3 seconds after the &#39;GO&#39; signal. If you did not tap the target within 3 seconds, bring the chopstick&#39;s tip to the home position and wait for the next trial. You will perform ten trials with a 10-second break between trials. Do you have any questions? [Address any questions that the participant has, then proceed to familiarization trial] You will have three trials as a practice. [After the practice trials, proceed to the actual trials] Now, we will perform actual trials. Try to reach and tap as quickly as you can.&#34;</li>
		</ol>
		</li>
		<li>Play the auditory cue signal audio file with a computer to familiarize the participant with the cue.</li>
		<li>Perform three familiarization trials.</li>
		<li>Instruct the participant to be ready for the task performance. Ensure the participant fully understands the task performance procedure.</li>
		<li>Start motion capture recording with the motion capture data acquisition software.</li>
		<li>Play the auditory cue audio file with a computer.</li>
		<li>Perform 10 trials.</li>
		<li>Stop motion capture recording.</li>
		<li>Take a 2-minute break.</li>
	</ol>
	</li>
	<li>Perform the task condition 2 - Reaching and Pointing to a small target.
	<ol>
		<li>Instruct the participant to hold a chopstick with the dominant hand (non-disabled adults) or the paretic hand (stroke participants). The participant will place the tip of a chopstick touching at the center of the home position. Ask the participant to maintain the upright trunk posture at the beginning.</li>
		<li>Fixate the task condition template paper at the designated area on the table. For this task, the target square size is 0.3 X 0.3 cm2. The target position is located 20 in front of the home position.</li>
		<li>Describe the task instruction.
		<ol>
			<li>State the following: &#34;The goal of this task is the same as the previous task: reach and tap with the chopstick&#39;s tip the target as quickly and accurately as you can. We will use a smaller target [indicate the target]. The instruction is the same as the previous task. When you hear a &#39;GO&#39; signal, reach and tap the target [indicate the target] with the chopstick&#39;s tip as quickly as possible. Try to tap the center of the target as much as you can. Do you have any questions? [Address any questions that the participant has, then proceed to familiarization trial] You will have three trials as a practice. [After the familiarization trials, proceed to the actual trials] Now, we will perform actual trials. Try to reach and tap as quickly as you can.&#34;</li>
		</ol>
		</li>
		<li>Play the auditory cue signal audio file with a computer to familiarize the participant with the cue.</li>
		<li>Perform three familiarization trials.</li>
		<li>Instruct participant to be ready for the task performance. Ensure the participant fully understands the task performance procedure.</li>
		<li>Start motion capture recording with the motion capture data acquisition software.</li>
		<li>Play the auditory cue audio file with a computer.</li>
		<li>Perform 10 trials.</li>
		<li>Stop motion capture recording.</li>
		<li>Take a 2-minute break.</li>
	</ol>
	</li>
	<li>Perform the task condition 3 - Reaching and Picking up a large target object.
	<ol>
		<li>Instruct the participant to hold a pair of chopsticks with the dominant hand (non-disabled adults) or the paretic hand (stroke participants). The participant will place the tips of chopsticks touching at the center of the home position. Ask the participant to maintain upright trunk posture at the beginning.</li>
		<li>Fixate the task condition template paper at the designated area on the table. For this task, the target object is a plastic cube 1 cm on edge. The target object is located 20 in front of the home position.</li>
		<li>Place the target object on the target area.</li>
		<li>Describe the task instructions.
		<ol>
			<li>State the following: &#34;The goal of this task is to reach and pick up a plastic cube [indicate the cube] with a pair of chopsticks as quickly as possible, about an inch in height without dropping. You will hold a pair of chopsticks with your right (or left) [indicate the performing hand]. Place the chopsticks&#39; tips on the home position [indicate the home position]. When you hear a &#39;GO&#39; signal, reach and pick up the cube [indicate the target] with the chopsticks as quickly as you can, about an inch in height. You will have three seconds to pick up the target. I will give you a &#39;STOP&#39; signal 3 seconds after the &#39;GO&#39; signal. If you did not pick up the target within 3 seconds, bring the chopsticks&#39; tips to the home position and wait for the next trial. You will perform ten trials with a 10-second break between trials. Do you have any questions? [Address any questions that the participant has, then proceed to familiarization trial] You will have three trials as a practice. [After the familiarization trials, proceed to the actual trials] Now, we will perform actual trials. Try to reach and pick up as quickly as you can.&#34;</li>
		</ol>
		</li>
		<li>Play the auditory cue signal audio file with a computer to familiarize the participant with the cue.</li>
		<li>Perform three familiarization trials.</li>
		<li>Instruct participant to be ready for the task performance. Ensure the participant fully understands the task performance procedure.</li>
		<li>Start motion capture recording with the motion capture data acquisition software.</li>
		<li>Play the auditory cue audio file with a computer.</li>
		<li>Perform 10 trials.</li>
		<li>Stop motion capture recording.</li>
		<li>Take a 2-minute break.</li>
	</ol>
	</li>
	<li>Perform the task condition 4 - Reaching and Picking up a small target object.
	<ol>
		<li>Instruct the participant to hold a pair of chopsticks with the dominant hand (non-disabled adults) or the paretic hand (stroke participants). The participant will place the tips of chopsticks touching at the center of the home position. Ask the participant to maintain upright trunk posture at the beginning.</li>
		<li>Fixate the task condition template paper at the designated area on the table. For this task, the target object is a plastic cube 0.3 cm on edge. The target object is located 20 in front of the home position.</li>
		<li>Place the target object on the target area.</li>
		<li>Describe the task instructions.
		<ol>
			<li>State the following: &#34;The goal of this task is the same as the previous task: reach and pick up a plastic cube with a pair of chopsticks as quickly as you can. We will use a smaller plastic cube [indicate the target]. The instruction is the same as the previous task. When you hear a &#39;GO&#39; signal, reach and pick up the cube [indicate the target] with chopsticks as quickly as possible. Do you have any questions? [Address any questions that the participant has, then proceed to familiarization trial] You will have three trials as a practice. [After the familiarization trials, proceed to the actual trials] Now, we will perform actual trials. Try to reach and tap as quickly as you can.&#34;</li>
		</ol>
		</li>
		<li>Play the auditory cue signal audio file with a computer to familiarize the participant with the cue.</li>
		<li>Perform three familiarization trials.</li>
		<li>Ask participant to be ready for the task performance. Make sure the participant fully understands the task performance procedure.</li>
		<li>Start motion capture recording with the motion capture data acquisition software.</li>
		<li>Play the auditory cue audio file with a computer.</li>
		<li>Perform the actual 10 trials.</li>
		<li>Stop motion capture recording.</li>
		<li>Take a 2-minute break.</li>
	</ol>
	</li>
	<li>Perform the Intrinsic motivation inventory (IMI) for the use of chopsticks using online survey platform.</li>
</ol>
6. Kinematic data analysis
<ol>
	<li>Export the data of the following landmarks from the motion capture data acquisition software. Export position data in the x-, y-, and z-axes as a text file for each task condition. 
	Tip of a chopstick 
	Home position on the table 
	Target position on the table 
	Hands 
	Elbow joints 
	Shoulder joints (glenohumeral joints) 
	Trunk (at C7)</li>
	<li>Preprocess the kinematic data.
	<ol>
		<li>Use custom programming script to process the kinematic data.</li>
		<li>Filter and smooth the raw position data using a 3rd order Butterworth low pass filter with a 3 Hz cutoff.</li>
		<li>Calculate the resultant of x-, y-, and z-direction position of the performing hand.</li>
	</ol>
	</li>
	<li>Determine movement onset and offset of each goal-directed arm reach.
	<ol>
		<li>To determine the reaching movement onset and offset, use the tangential velocity (the first derivative of the position data) from the resultant of the 3-dimensional position of the performing hand.</li>
		<li>Define movement onset as the first frame of the reach, where the tangential velocity is above 0.01 m/s.</li>
		<li>Define movement offset as the last frame of the reach, where the tangential velocity is above 0.01 m/s.</li>
		<li>Inspect the individual reaching movement onset and offset visually to ensure the onset and offset are correctly labeled.</li>
	</ol>
	</li>
	<li>Determine the peak velocity. The peak velocity is defined as the maximum tangential velocity amplitude of the trial that exceeds the amplitude of 0.2 m/s, and the time interval between 2 peaks must be at least 2 seconds13.</li>
	<li>Calculate kinematic variables of reaching movements.
	<ol>
		<li>Calculate movement duration (MD). Calculate the time difference between movement onset and offset13.</li>
		<li>Calculate peak velocity (PV). Calculate the highest velocity during each of the reaches.</li>
		<li>Calculate absolute and relative time to peak velocity (TTPV and TTPV % of movement duration)13.
		<ol>
			<li>Calculate the time difference between movement onset and peak velocity (absolute TTPV).</li>
			<li>Calculate the percentage of TTPV relative to movement duration (relative TTPV).</li>
		</ol>
		</li>
		<li>Calculate log dimensionless jerk.
		<ol>
			<li>Calculate the third derivative from the resultant of the 3-dimensional position of the performing hand, then calculate the log dimensionless jerk of each arm reaching movement.</li>
		</ol>
		</li>
		<li>Calculate trunk displacement during goal-directed arm reaching movement9,14.
		<ol>
			<li>Calculate the trunk displacement.
			<ol>
				<li>Calculate the distance difference of the trunk landmark between movement onset and offset. Use the following equation. 
				<img alt="Equation 1" src="/files/ftp_upload/61940/61940eq01v4.jpg" /> 
				Where X, Y, and Z are the trunk landmark positions in x-, y-, and z-axis, respectively; 1 is the time frame at the reaching movement onset; k is the time frame at the reaching movement offset.</li>
			</ol>
			</li>
			<li>Calculate shoulder trajectory length.
			<ol>
				<li>Calculate the shoulder landmark&#39;s travel distance between arm reaching movement onset and offset. The shoulder landmark is a virtual landmark digitized from the motion capture data acquisition software using the upper extremity skeleton model. Use the following equation for the shoulder trajectory length calculation. 
				<img alt="Equation 2" src="/files/ftp_upload/61940/61940eq2b.jpg" /> 
				Where X, Y,and Z are the positions of the shoulder landmark in x-, y-, and z-axis, respectively; t is the time frame; t=1 is the time frame at the reaching movement onset; t=k is the time frame at the reaching movement offset</li>
			</ol>
			</li>
		</ol>
		</li>
	</ol>
	</li>
</ol>

<ol>
	<li>Spinazzola, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Impairments+of+trunk+movements+following+left+or+right+hemisphere+lesions:+dissociation+between+apraxic+errors+and+postural+instability.">Impairments of trunk movements following left or right hemisphere lesions: dissociation between apraxic errors and postural instability.</a> Brain. 126 (12), 2656-2666 (2003).</li><li>Michaelsen, S. M., Jacobs, S., Roby-Brami, A., Levin, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Compensation+for+distal+impairments+of+grasping+in+adults+with+hemiparesis.">Compensation for distal impairments of grasping in adults with hemiparesis.</a> Experimental Brain Research. 157 (2), 162-173 (2004).</li><li>Saposnik, G., Levin, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SORCan+SORC.+Virtual+Reality+in+Stroke+Rehabilitation+A+Meta-Analysis+and+Implications+for+Clinicians.">SORCan SORC. Virtual Reality in Stroke Rehabilitation A Meta-Analysis and Implications for Clinicians.</a> Stroke. 42 (5), 1380-1386 (2011).</li><li>Levin, M. F., Snir, O., Liebermann, D. G., Weingarden, H., Weiss, P. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Virtual+Reality+Versus+Conventional+Treatment+of+Reaching+Ability+in+Chronic+Stroke:+Clinical+Feasibility+Study.">Virtual Reality Versus Conventional Treatment of Reaching Ability in Chronic Stroke: Clinical Feasibility Study.</a> Neurology and Therapy. 1 (1), 3 (2012).</li><li>Knaut, L. A., Subramanian, S. K., McFadyen, B. J., Bourbonnais, D., Levin, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinematics+of+pointing+movements+made+in+a+virtual+versus+a+physical+3-dimensional+environment+in+healthy+and+stroke+subjects.">Kinematics of pointing movements made in a virtual versus a physical 3-dimensional environment in healthy and stroke subjects.</a> Archives of Physical Medicine and Rehabilitation. 90 (5), 793-802 (2009).</li><li>Mastos, M., Miller, K., Eliasson, A. C., Imms, C., Mastos, M., Eliasson, A. C., Imms, C. M. K., Mastos Miller, K., Eliasson, A. C., Imms, C. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Goal-directed+training:+linking+theories+of+treatment+to+clinical+practice+for+improved+functional+activities+in+daily+life.">Goal-directed training: linking theories of treatment to clinical practice for improved functional activities in daily life.</a> Clinical Rehabilitation. 21 (1), 47-55 (2007).</li><li>Harris, C. M., Wolpert, D. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Signal-dependent+noise+determines+motor+planning.">Signal-dependent noise determines motor planning.</a> Nature. 394, 780-784 (1998).</li><li>Gentilucci, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Object+motor+representation+and+reaching-grasping+control.">Object motor representation and reaching-grasping control.</a> Neuropsychologia. 40 (8), 1139-1153 (2002).</li><li>Subramanian, S. K., Yamanaka, J., Chilingaryan, G., Levin, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Validity+of+Movement+Pattern+Kinematics+as+Measures+of+Arm+Motor+Impairment+Poststroke.">Validity of Movement Pattern Kinematics as Measures of Arm Motor Impairment Poststroke.</a> Stroke. 41 (10), 2303-2308 (2010).</li><li>Strenge, H., Niederberger, U., Seelhorst, U. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Correlation+between+Tests+of+Attention+and+Performance+on+Grooved+and+Purdue+Pegboards+in+Normal+Subjects.">Correlation between Tests of Attention and Performance on Grooved and Purdue Pegboards in Normal Subjects.</a> Perceptual and Motor Skills. 95 (2), 507-514 (2002).</li><li>Lin, J. -. H., Hsu, M. -. J., Sheu, C. -. F., 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=Psychometric+comparisons+of+4+measures+for+assessing+upper-extremity+function+in+people+with+stroke.">Psychometric comparisons of 4 measures for assessing upper-extremity function in people with stroke.</a> Physical Therapy. 89 (8), 840-850 (2009).</li><li>See, J., Dodakian, L., Chou, C., 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=A+standardized+approach+to+the+fugl-meyer+assessment+and+its+implications+for+clinical+trials.">A standardized approach to the fugl-meyer assessment and its implications for clinical trials.</a> Neurorehabilitation and Neural Repair. 27 (8), 732-741 (2013).</li><li>Murphy, M. A., Will&#233;n, C., Sunnerhagen, K. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Kinematic+Variables+Quantifying+Upper-Extremity+Performance+After+Stroke+During+Reaching+and+Drinking+From+a+Glass.">Kinematic Variables Quantifying Upper-Extremity Performance After Stroke During Reaching and Drinking From a Glass.</a> Neurorehabilitation and Neural Repair. 25 (1), 71-80 (2011).</li><li>Michaelsen, S. M., Jacobs, S., Roby-Brami, A., Levin, M. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Compensation+for+distal+impairments+of+grasping+in+adults+with+hemiparesis.">Compensation for distal impairments of grasping in adults with hemiparesis.</a> Experimental Brain Research. 157, 162-173 (2004).</li><li>J&#228;rvel&#228;inen, J., Sch&#252;rmann, M., Hari, R., Jarvelainen, J., Schurmann, M., Hari, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Activation+of+the+human+primary+motor+cortex+during+observation+of+tool+use.">Activation of the human primary motor cortex during observation of tool use.</a> Neuroimage. 23 (1), 187-192 (2004).</li><li>Imazu, S., Sugio, T., Tanaka, S., Inui, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Differences+between+actual+and+imagined+usage+of+chopsticks:+An+fMRI+study.">Differences between actual and imagined usage of chopsticks: An fMRI study.</a> Cortex. 43 (3), 301-307 (2007).</li><li>Ishii, R., Schulz, M., Xjang, J., 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=MEG+study+of+lang-term+cortical+reoganization+of+senorimotor+areas+with+respect+to+using+chopsticks.">MEG study of lang-term cortical reoganization of senorimotor areas with respect to using chopsticks.</a> Neuroreport. 13 (16), 2155-2159 (2002).</li><li>Chen, H. M., Chang, 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=The+skill+components+of+a+therapeutic+chopsticks+task+and+their+relationship+with+hand+function+tests.">The skill components of a therapeutic chopsticks task and their relationship with hand function tests.</a> Kaohsiung Journal of Medical Sciences. 15 (12), 704-709 (1999).</li><li>Shin, S., Demura, S., Aoki, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Effects+of+prior+use+of+chopsticks+on+two+different+types+of+dexterity+tests:+Moving+Beans+Test+and+Purdue+Pegboard.">Effects of prior use of chopsticks on two different types of dexterity tests: Moving Beans Test and Purdue Pegboard.</a> Perceptual and Motor Skills. 108 (2), 392-398 (2009).</li><li>Ma, H. -. i., Trombly, C. A., Robinson-Podolski, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Effect+of+Context+on+Skill+Acquisition+and+Transfer.">The Effect of Context on Skill Acquisition and Transfer.</a> American Journal of Occupational Therapy. 53 (2), 138-144 (1999).</li><li>Rosenbaum, D. A., Engelbrecht, S. E., Bushe, M. M., Loukopoulos, L. D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Knowledge+Model+for+Selecting+and+Producing+Reaching+Movements.">Knowledge Model for Selecting and Producing Reaching Movements.</a> Journal of Motor Behavior. 25 (3), 217-227 (1993).</li></ol>

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Preliminary results support that this protocol may be appropriate to investigate the impact of task complexity on trunk compensation and goal-directed arm reaching kinematics in both non-disabled adults and chronic stroke survivors.
These representative results also support that this protocol may be appropriate to determine the kinematic differences in goal-directed arm reaches between non-disabled adults and chronic stroke survivors. These findings are consistent with previous studies that ch...

Trunk movement is the most common strategy to compensate for limited degrees of freedom in the elbow and shoulder in individuals with post-stroke upper extremity (UE) motor deficits1,2. Previous studies have shown that post-stroke individuals employ different movement strategies in different motor task environments3,4,5. Dynamic systems motor control theory explains that movements emerge from internal individual factors and external factors, such as task conditions and environment6. Further, Fitt&#39;s law explains the relationship between task difficulty and movement speed, with a tendency to perform more difficult tasks with slower speeds7. In terms of goal-directed arm reaching tasks, Gentilucci reported that people slow down their reaching movements when they reach and grasp a smaller object compared to a larger object8. However, the impact of task complexity on goal-directed arm reaching kinematics and compensatory movement strategies in chronic stroke survivors is not well understood. A previous study that examined pointing and grasping tasks in chronic stroke survivors demonstrated that differences in kinematic variables between two different tasks explained differences in UE motor impairment as measured by the Fugl-Meyer Upper Extremity Score9. However, this study did not directly compare how movement strategies are different in terms of kinematic variables between pointing and grasping tasks. A better understanding of the impact of task conditions on compensatory movement strategies in consideration of individual motor impairment level is crucial to design effective treatment sessions to minimize compensatory movements and maximize restitution of motor impairment. Therefore, it is imperative to investigate how task conditions, specifically task complexity, impact movement strategies in individuals with post-stroke motor impairment. This proposed study protocol will investigate the impact of task conditions on goal-directed arm reaching kinematics in non-disabled adults and stroke survivors. The aims of this protocol are two-fold: 1) to investigate whether the task complexity influences trunk compensation and goal-directed arm reaching kinematics in chronic stroke survivors; 2) to determine if this protocol can differentiate the kinematics of goal-directed arm reaches between non-disabled adults and chronic stroke survivors.

<table><tbody><tr><td>A pair of chopsticks</td><td>NA</td><td>NA</td><td>20 cm length, one chopstick had the passive motion capture markers (custom made)</td></tr><tr><td>Auditory cues for motor tasks</td><td>NA</td><td>NA</td><td>Custom made audio file are played on a smart phone</td></tr><tr><td>Matlab R2018b software</td><td>Mathworks</td><td></td><td></td></tr><tr><td>MotionMonitor v 8.52 Software</td><td>Innovative Sports Training, Inc., Chicago, IL</td><td></td><td></td></tr><tr><td>Perdue Pegboard Test</td><td></td><td></td><td></td></tr><tr><td>Plastic cubes (0.3 cm on edge)</td><td>NA</td><td>NA</td><td>Custom made plastic cubes with 0.3 cm on edge. These were made using 3D printer</td></tr><tr><td>Plastic cubes (1cm on edge)</td><td>NA</td><td>NA</td><td>Custom made plastic cubes with 1 cm on edge. These were made using 3D printer</td></tr><tr><td>Template print</td><td>NA</td><td>NA</td><td>Custom made templates of the motor tasks, including home position, outlines of target positions.</td></tr><tr><td>Vicon 512 Motion-analysis System and Work station v5.2 software</td><td>OMG plc, Oxford, UK</td><td></td><td></td></tr></tbody></table>

the impact of motor task conditions on goal-directed arm reaching kinematics and trunk compensation in chronic stroke survivors

Trunk compensation is the most common movement strategy to substitute for upper extremity (UE) motor deficits in chronic stroke survivors. There is a lack of evidence examining how task conditions impact trunk compensation and goal-directed arm reaching kinematics. This protocol aims to investigate the impact of task conditions, including task difficulty and complexity, on goal-directed arm reaching kinematics. Two non-disabled young adults and two chronic stroke survivors with mild UE motor impairment were recruited for testing the protocol. Each participant performed goal-directed arm reaches with four different task conditions (2 task difficulties [large vs. small targets] X 2 task complexities [pointing vs. picking up]). The task goal was to reach and point at a target or pick up an object located 20 cm in front of the home position as quickly as possible with a stylus or a pair of chopsticks, respectively, in response to an auditory cue. Participants performed ten reaches per task condition. A 3-dimensional motion capture camera system was used to record trunk and arm kinematics. Representative results showed that there was a significant increase in movement duration, movement jerkiness, and trunk compensation as a function of task complexity, but not task difficulty in all participants. Chronic stroke survivors showed significantly slower, jerkier, and more feedback-dependent arm reaches and significantly more compensatory trunk movements than non-disabled adults. Our representative results support that this protocol can be used to investigate the impact of task conditions on motor control strategies in chronic stroke survivors with mild UE motor impairment.

These results are preliminary data from two non-disabled young adults and two chronic stroke survivors with mild motor impairment (Fugl-Meyer Scores of these two participants were above 60 out of 66). Non-disabled participants were right-handed and performed the tasks with their right hand. Stroke participants were also right-handed before the stroke and both had right hemiparesis. They also performed the task with their right hand. These kinematic variables between populations and between target conditions were compared...

Watch this Scientific Journal Video about The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors at JoVE.com

The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors

This protocol is intended to investigate the impact of task conditions on movement strategies in chronic stroke survivors. Further, this protocol can be used to examine if a restriction in elbow extension induced by neuromuscular electrical stimulation causes trunk compensation during goal-directed arm reaches in non-disabled adults.

Trunk compensation is the most common movement strategy to substitute for upper extremity (UE) motor deficits in chronic stroke survivors. There is a lack ...

the-impact-motor-task-conditions-on-goal-directed-arm-reaching

Research

JoVE Journal

Neuroscience

3.5K Views.  SUNY Upstate Medical University. Beroerte is een belangrijke oorzaak van langdurige invaliditeit. Trunk compensatie is de meest voorkomende bewegingsstrategie ter vervanging van beperkte arm bereiken omvang tijdens doelgerichte arm bereiken voor dagelijkse activiteiten. Er zijn een aantal factoren die van invloed zijn op motorische controlestrategieën, zoals individuele, omgevings- en testconditiefactoren.Eerdere studies hebben zich gericht op de individuen en omgevingsfactoren. De testconditiefactoren zijn echter ni...

Video: The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors

Compensatory Limb Use and Behavioral Assessment of Motor Skill Learning Following Sensorimotor Cortex Injury in a Mouse Model of Ischemic Stroke

Mouse models have become increasingly popular in the field of behavioral neuroscience, and specifically in studies of experimental stroke. As models advance, it is important to develop sensitive behavioral measures specific to the mouse. The present protocol describes a skilled motor task for use in mouse models of stroke. The Pasta Matrix Reaching Task functions as a versatile and sensitive behavioral assay that permits experimenters to collect accurate outcome data and manipulate limb use to mimic human clinical phenomena including compensatory strategies (i.e., learned non-use) and focused rehabilitative training. When combined with neuroanatomical tools, this task also permits researchers to explore the mechanisms that support behavioral recovery of function (or lack thereof) following stroke. The task is both simple and affordable to set up and conduct, offering a variety of training and testing options for numerous research questions concerning functional outcome following injury. Though the task has been applied to mouse models of stroke, it may also be beneficial in studies of functional outcome in other upper extremity injury models.

Mouse models have become increasingly popular in studies of behavioral neuroscience. As models advance, it is important to develop sensitive behavioral measures specific to the mouse. This protocol describes the Pasta Matrix Reaching Task, which is a skilled motor task for use in mouse models of stroke.

Mouse models have become increasingly popular in the field of behavioral neuroscience, and specifically in studies of experimental stroke. As models ...

Behavior

Mobile Game-based Virtual Reality Program for Upper Extremity Stroke Rehabilitation

Stroke rehabilitation requires repetitive, intensive, goal-oriented therapy. Virtual reality (VR) has the potential to satisfy these requirements. Game-based therapy can promote patients&#39; engagement in rehabilitation therapy as a more interesting and a motivating tool. Mobile devices such as smartphones and tablet PCs can provide personalized home-based therapy with interactive communication between patients and clinicians. In this study, a mobile VR upper extremity rehabilitation program using game applications was developed. The findings from the study show that the mobile game-based VR program effectively promotes upper extremity recovery in patients with stroke. In addition, patients completed two weeks of treatment using the program without adverse effects and were generally satisfied with the program. This mobile game-based VR upper extremity rehabilitation program can substitute for some parts of the conventional therapy that are delivered one-on-one by an occupational therapist. This time-efficient, easy to implement, and clinically effective program would be a good candidate tool for tele-rehabilitation for upper extremity recovery in patients with stroke. Patients and therapists can collaborate remotely through these e-health rehabilitation programs while reducing economic and social costs.

Here, we present a protocol to develop and apply a mobile game-based virtual reality program for the recovery of upper limb dysfunction in patients with stroke. The present study shows that the mobile program is feasible and effectively promotes upper limb recovery in stroke patients.

Stroke rehabilitation requires repetitive, intensive, goal-oriented therapy. Virtual reality (VR) has the potential to satisfy these requirements. ...

Kinematic Analysis Using 3D Motion Capture of Drinking Task in People With and Without Upper-extremity Impairments

Kinematic analysis is a powerful method for objective assessment of upper extremity movements in a three-dimensional (3D) space. Three-dimensional motion capture with an optoelectronic camera system is considered as golden standard for kinematic movement analysis and is increasingly used as outcome measure to evaluate the movement performance and quality after an injury or disease involving upper extremity movements. This article describes a standardized protocol for kinematic analysis of drinking task applied in individuals with upper extremity impairments after stroke. The drinking task incorporates reaching, grasping and lifting a cup from a table to take a drink, placing the cup back, and moving the hand back to the edge of the table. The sitting position is standardized to the individual&#39;s body size and the task is performed in a comfortable self-paced speed and compensatory movements are not constrained. The intention is to keep the task natural and close to a real-life situation to improve the ecological validity of the protocol. A 5-camera motion capture system is used to gather 3D coordinate positions from 9 retroreflective markers positioned on anatomical landmarks of the arm, trunk, and face. A simple single marker placement is used to ensure the feasibility of the protocol in clinical settings. Custom-made Matlab software provides automated and fast analyses of movement data. Temporal kinematics of movement time, velocity, peak velocity, time of peak velocity, and smoothness (number of movement units) along with spatial angular kinematics of shoulder and elbow joint as well as trunk movements are calculated. The drinking task is a valid assessment for individuals with moderate and mild upper extremity impairment. The construct, discriminative and concurrent validity along with responsiveness (sensitivity to change) of the kinematic variables obtained from the drinking task have been established.

This protocol describes an objective method to evaluate the movement performance and sensorimotor function of the upper extremity applied to individuals with stroke and healthy controls. A standardized test procedure, kinematic analysis and outcome variables for three-dimensional motion capture of drinking task are provided.

Kinematic analysis is a powerful method for objective assessment of upper extremity movements in a three-dimensional (3D) space. Three-dimensional motion ...

Motor Dual-Tasks for Gait Analysis and Evaluation in Post-Stroke Patients

Eighteen stroke patients were recruited for this study involving the evaluation of cognition and walking ability and multitask gait analysis. Multitask gait analysis consisted of a single walking task (Task 0), a simple motor dual-task (water-holding, Task 1), and a complex motor dual-task (crossing obstacles, Task 2). The task of crossing obstacles was considered to be equivalent to the combination of a simple walking task and a complex motor task as it involved more nervous system, skeletal movement, and cognitive resources. To eliminate heterogeneity in the results of the gait analysis of the stroke patients, the dual-task gait cost values were calculated for various kinematic parameters. The major differences were observed in the proximal joint angles, especially in the angles of the trunk, pelvis, and hip joints, which were significantly larger in the dual motor tasks than in the single walking task. This research protocol aims to provide a basis for the clinical diagnosis of gait function and an in-depth study of motor control in stroke patients with motor control deficits through the analyses of dual-motor walking tasks.

This paper presents a protocol specifically for dual motor task gait analysis in stroke patients with motor control deficits.

Eighteen stroke patients were recruited for this study involving the evaluation of cognition and walking ability and multitask gait analysis. Multitask ...

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.

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 ...

Medicine

Evaluating Brain Activation by fNIRS During a Lower Limb Robotic Therapy Session

An Experiment Using Functional Near-Infrared Spectroscopy and Robot-Assisted Multi-Joint Pointing Movements of the Lower Limb

Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown promise in helping stroke patients regain lost motor functions. One potential avenue for increasing the understanding of how motor recovery occurs is to study brain activation during the movements that are targeted by therapy in healthy individuals. Functional Near-Infrared Spectroscopy (fNIRS) has emerged as a promising neuroimaging technique for examining neural underpinnings of motor function. This study aimed to investigate fNIRS neural correlates of complex lower limb movements in healthy subjects. Participants were asked to perform cycles of rest and movement for 6 min using a robotic device for motor rehabilitation. The task required coordinated knee and ankle joint movements to point to targets displayed on a computer screen. Two experimental conditions with different levels of movement assistance provided by the robot were explored. The results showed that the fNIRS protocol effectively detected brain regions associated with motor control during the task. Notably, all subjects exhibited greater activation in the contralateral premotor area during the no-assistance condition compared to the assisted condition. In conclusion, fNIRS appears to be a valuable approach for detecting changes in oxyhemoglobin concentration associated with multi-joint pointing movements of the lower limb. This research might contribute to the understanding of stroke motor recovery mechanisms and might pave the way for improved rehabilitation treatments for stroke patients. However, further research is needed to fully elucidate the potential of fNIRS in studying motor function and its applications in clinical settings.

Author Spotlight: Assessing Brain Activity in Robotic-Assisted Lower Limb Rehabilitation Using fNIRS

It is estimated that 1 in 6 individuals worldwide will have a stroke in their lifetime, causing long-term disability, whose rehabilitation mechanisms are still poorly understood. This study proposes a protocol to evaluate brain activation by functional near-infrared spectroscopy (fNIRS) during a lower limb robotic therapy session.

Stroke affects approximately 17 million individuals worldwide each year and is a leading cause of long-term disability. Robotic therapy has shown promise ...

Enhancing Stroke Rehabilitation with Virtual Reality-Based Occupational Training

Cognitive Function and Upper Limb Rehabilitation Training Post-Stroke Using a Digital Occupational Training System

Stroke rehabilitation often requires frequent and intensive therapy to improve functional recovery. Virtual reality (VR) technology has shown the potential to meet these demands by providing engaging and motivating therapy options. The digital occupational training system is a VR application that utilizes cutting-edge technologies, including multi-touch screens, virtual reality, and human-computer interaction, to offer diverse training techniques for advanced cognitive capacity and hand-eye coordination abilities. The objective of this study was to assess the effectiveness of this program in enhancing cognitive function and upper extremity rehabilitation in stroke patients. The training and assessment consist of five cognitive modules covering perception, attention, memory, logical reasoning, and calculation, along with hand-eye coordination training. This research indicates that after eight weeks of training, the digital occupational training system can significantly improve cognitive function, daily living skills, attention, and self-care abilities in stroke patients. This software can be employed as a time-saving and clinically effective rehabilitation aid to complement traditional one-on-one occupational therapy sessions. In summary, the digital occupational training system shows promise and offers potential financial benefits as a tool to support the functional recovery of stroke patients.

Author Spotlight: Rehabilitation of Stroke Patients With a Digital Occupational Training System

The current protocol outlines how the VR-based digital occupational training system enhances the rehabilitation of patients with cognitive impairment and upper limb dysfunction following a stroke.

Stroke rehabilitation often requires frequent and intensive therapy to improve functional recovery. Virtual reality (VR) technology has shown the ...

Functional OT and Near-IR Spectroscopy to Study Brain Function Remodeling

Investigating the Effect of Different Types of Exercise on Upper Limb Functional Recovery in Patients with Right Hemisphere Damage Based on fNIRS

To investigate the effects of functional occupational therapy (FOT) combined with different types of exercise on upper limb motor function recovery and brain function remodeling in patients with right hemisphere damage (RHD) by analyzing functional near-infrared spectroscopy (fNIRS). Patients (n = 32) with RHD at Beijing Bo'ai Hospital were recruited and randomly allocated to receive either FOT combined with passive motion (N=16) or FOT combined with assisted active movement (N=16). The passive motion group (FOT-PM) received functional occupational therapy for 20 min and passive exercise for 10 min in each session, while the assisted active movement group (FOT-AAM) received functional occupational therapy for 20 min and assisted active exercise for 10 min. Both groups received conventional drug therapy and other rehabilitation therapy. Treatment was performed once a day, 5 times a week for 4 weeks. The recovery of motor function and activities of daily living (ADL) was assessed using Fugl-Meyer Assessment upper extremity (FMA-UE) and modified Barthel index (MBI) before and after treatment, and brain activation of the bilateral motor area was analyzed with fNIRS. The findings suggested that FOT combined with AAM was more effective than FOT combined with PM in improving the motor function of RHD patients' upper limbs and fingers, improving their ability to perform activities of daily living, and facilitating brain function remodeling of the motor area.

Author Spotlight: Advancing Upper Limb Rehabilitation in Patients with Right Hemisphere Damage Using Assisted Active Exercise

Here, we investigate the effect of functional occupational therapy combined with assisted active or passive motion on the upper limb function of patients with right hemisphere damage and explore the effect of functional near-infrared spectroscopy on brain function remodeling.

To investigate the effects of functional occupational therapy (FOT) combined with different types of exercise on upper limb motor function recovery and ...

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 ...

The Impact of Motor Task Conditions on Goal-Directed Arm Reaching Kinematics and Trunk Compensation in Chronic Stroke Survivors

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