This work is supported by the National Natural Science Foundation of China under Grant U1913207 and by the Program for HUST Academic Frontier Youth Team. The authors would like to thank the support from these foundations.

This protocol has been approved by the Ethics Review Board of Union Hospital, Tongji Medical College, Huazhong University of Science and Technology. Patients with upper limb functional disorders who met the diagnostic criteria and were receiving treatment at the author&#39;s hospital&#39;s rehabilitation department outpatient and inpatient units were selected as participants. The patients&#39; motor function recovery was assessed according to the Brunnstrom recovery stages21, and patients in stages 3-5 were chosen to participate in the experiments. Written informed consent was obtained from the patients who participated in the study. The procedure includes mold design for the pneumatic gripper, the fabrication process of the pneumatic gripper based on cured silicone rubber, integration of portable devices, and software and hardware implementation for grasp intention detection. Except for silicone rubber and common fabrics, all wearable components are produced using 3D printing technology (see Supplementary Coding Files 1-5).
1. Designing and fabricating the pneumatic gripper
<ol>
	<li>Assemble the pre-designed mold22 as shown in Figure 1A,B. Then use hot melt glue to secure the glass fibers at the designated positions in the mold, as depicted in Figure 1C. Ensure to use hot melt glue to seal any potential areas that may cause silicone leakage.</li>
	<li>Weigh an appropriate amount of Component A and Component B of the silicone elastomer (9:1 by weight) (see Table of Materials), and mix them in the specified ratio. After mixing, utilize a vacuum mixing and degassing machine with a variable centrifugal force, determined by the internal preset program of the machine. Once the mixture is ready, promptly inject it into the assembled mold, as illustrated in Figure 1D. 
	NOTE: The variable centrifugal force is controlled by the vacuum mixing and degassing machine through its internal preset program (see Table of Materials). The centrifugal force must be incrementally increased to ensure thorough mixing of the silicone rubber and the removal of any trapped air bubbles.</li>
	<li>Allow the mold to sit for approximately 30 s, then place it in a vacuum dryer for about 1 min to enable any small air bubbles in the silicone rubber to escape. Remove the mold from the dryer and place it as a whole in a thermostatic chamber set at 30 &#176;C for 12 h, allowing the silicone rubber to cure.</li>
	<li>Repeat the steps outlined in the second step by injecting the mixed silicone rubber into the mold shown in Figure 1E. Next, place the demolded rubber body shown in Figure 1F into the mold filled with silicone rubber. Put the entire assembly in a thermostatic chamber set at 30 &#176;C for 12 h to allow the silicone rubber to cure.</li>
	<li>Remove the cured silicone rubber body from the mold and trim off any excess silicone rubber. The fabrication of the flexible gripper is now complete. 
	&#8203;NOTE: The cavity consists of two sets of pneumatic grids, which are independent of each other. Due to the significant difference in elastic modulus between the glass fibers and the corrugated structure, the pneumatic gripper bends inward when inflated, allowing for envelope-grasping actions. The fingertip is designed with a protrusion resembling an elephant trunk, enabling fingertip-grasping actions.</li>
</ol>
2. Assembling the wearable flexible supernumerary robotic limb
NOTE: The wearable supernumerary robotic limb includes a mini air pump, air valves, a single-chip microcomputer, pneumatic gripper, power supply, flexible bending sensors, a wearable glove, and accessories for pneumatic and electrical connections (see Table of Materials), as shown in Figure 2.
<ol>
	<li>Meticulously handcraft the wearable glove with the help of a tailor. Ensure it undergoes multiple iterations and improvements based on wearer feedback and the tailor&#39;s experience.</li>
	<li>Secure the pneumatic gripper with 3D-printed parts and attach it to the appropriate position on the glove using adhesive tape.</li>
	<li>Embed three flexible bending sensors (see Table of Materials) as shown in Figure 3 into the glove. Place them on the index, middle, and ring fingers, respectively, aligning them with the backside of the fingers. Use a data acquisition card to record signals from the sensors.</li>
	<li>Amplify the sensor signals and route them to an Arduino (see Table of Materials). Process these signals using a sliding window and least squares filtering within the Arduino23. Utilize these estimated values as baseline data for intent detection.</li>
	<li>Place components such as the air pump, air valves, control board, and power supply into a backpack for portability. Refer to Figure 4 for a visual representation of the wearing effect.</li>
</ol>
3. Detecting the grasping intention
NOTE: When the wearer&#39;s fingers generate movement, the sensor feedback signal changes accordingly. It works by increasing the resistance in the circuit as the component bends more. Figure 5 shows the recorded signal values of the flexible bending sensor during the finger movement of one volunteer. The three curves correspond to the signals obtained from sensors placed on the three fingers. Patients with hemiparesis often have limited finger mobility, but the sensor is capable of detecting significant changes.
<ol>
	<li>Collect data on the range and pattern of sensor changes during finger movements. Select appropriate threshold values based on the detected sensor amplitude to control pump activation. Instruct participants to move their fingers freely within their range of ability. Determine the threshold values as the averages of the peak and valley values of the sensor feedback. 
	NOTE: When the sensor signal exceeds the set threshold value, the pump starts operating. The air pressure increases as the fingers bend further. Conversely, when the bending angle of the fingers decreases, and the sensor detects a signal below the threshold, the air valve releases the pressure to zero, and the pneumatic gripper releases.</li>
	<li>Ask the user to observe the state of the pneumatic gripper and determine the appropriate time to stop inflating the air and cease further finger bending.</li>
	<li>Repeat the above tests to establish a reasonable threshold and to become familiar with using this device.</li>
</ol>
4. Testing the device with healthy volunteers
<ol>
	<li>Enlist three healthy volunteers with normal upper limb motor abilities for the study to confirm the wearing and grasping effects of the prototype.</li>
	<li>Set the maximum air pressure for the pneumatic gripper to 100 kPa. Instruct the participants to flex and extend their fingers. Have the participants wear the prototype and conduct gripping and releasing experiments on objects of various shapes using the method mentioned earlier.</li>
	<li>Solicit feedback from the wearers regarding their experience and adjust the wearing scheme based on their suggestions. 
	&#8203;NOTE: As depicted in Figure 6, the participants successfully enveloped and grasped cylindrical objects of different sizes using the prototype. Additionally, they also completed fingertip grasping tasks on rectangular block-shaped objects.</li>
</ol>
5. Rehabilitation and grasp assistance for patients
<ol>
	<li>Evaluate the patients&#39; motor function recovery according to the Brunnstrom recovery stages21 by medical professionals. Only allow patients in stages 3-5 to participate in the experiments for rehabilitation training or daily assistance.</li>
	<li>Enlist six chronic hemiparetic patients to validate the reliability and effectiveness of the prototype. Instruct the patients to independently wear the glove (excluding the backpack) and move their fingers within their range of ability for calibrating the threshold values.</li>
	<li>During the rehabilitation phase, encourage patients to engage in various gripping tasks to exercise their finger muscles. Have the patients sit at the edge of a table and use the prototype to perform a series of grasping activities, including grasping a water bottle, a banana, a cube, and a toothbrush.</li>
	<li>Ask the patients to complete relevant survey questionnaires (Supplementary File 1) based on their personal experiences after the experiment. Assess the following six subjective feelings: confidence in the function of the system; ease of use; convenience and comfort of wearing it; effectiveness and usefulness for rehabilitation; effectiveness and usefulness in daily life; areas that still need improvement.</li>
	<li>Rate their responses on a scale of 1 to 5, where 1 represents strongly disagree and 5 represents strongly agree. Record the data and analyze the issues with the prototype and potential areas for improvement based on the questionnaire. 
	NOTE: This not only adds interest to the rehabilitation training but also enhances the patient&#39;s willingness to participate in the recovery process. In cases where patients have reached a stable condition but still struggle to perform gripping tasks with their fingers, the use of the robotic limb can assist in carrying out certain daily grasping actions required for everyday life.</li>
</ol>

Revolutionizing Stroke Rehabilitation with Enhanced Grasping and Finger Recovery

<ol>
	<li>Feigin, V. 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=Global,+regional,+and+national+burden+of+stroke+and+its+risk+factors,+1990-2019:+A+systematic+analysis+for+the+global+burden+of+disease+study+2019.">Global, regional, and national burden of stroke and its risk factors, 1990-2019: A systematic analysis for the global burden of disease study 2019.</a> The Lancet Neurology. 20 (10), 795-820 (2021).</li><li>Nakayma, H., J&#248;rgensen, H. S., Raaschou, H. O., Olsen, T. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Compensation+in+recovery+of+upper+extremity+function+after+stroke:+The+copenhagen+stroke+study.">Compensation in recovery of upper extremity function after stroke: The copenhagen stroke study.</a> Archives of Physical Medicine and Rehabilitation. 75 (8), 852-857 (1994).</li><li>Faria-Fortini, I., Michaelsen, S. M., Cassiano, J. G., Teixeira-Salmela, L. F. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Upper+extremity+function+in+stroke+subjects:+Relationships+between+the+international+classification+of+functioning,+disability,+and+health+domains.">Upper extremity function in stroke subjects: Relationships between the international classification of functioning, disability, and health domains.</a> Journal of Hand Therapy. 24 (3), 257-265 (2011).</li><li>Al-Fahaam, H., Davis, S., Nefti-Meziani, S., Theodoridis, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Novel+soft+bending+actuator-based+power+augmentation+hand+exoskeleton+controlled+by+human+intention.">Novel soft bending actuator-based power augmentation hand exoskeleton controlled by human intention.</a> Intelligent Service Robotics. 11, 247-268 (2018).</li><li>Thalman, C. M., Hsu, J., Snyder, L., Polygerinos, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=IEEE+International+Conference+on+Robotics+and+Automation+(ICRA).">IEEE International Conference on Robotics and Automation (ICRA).</a> , 8436-8442 (2019).</li><li>Miron, G., Plante, J. S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Design+principles+for+improved+fatigue+life+of+high-strain+pneumatic+artificial+muscles.">Design principles for improved fatigue life of high-strain pneumatic artificial muscles.</a> Soft Robotics. 3 (4), 177-185 (2016).</li><li>Yun, Y., 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=IEEE+International+Conference+on+Robotics+and+Automation+(ICRA).">IEEE International Conference on Robotics and Automation (ICRA).</a> , 2904-2910 (2017).</li><li>Tran, P., Jeong, S., Herrin, K. R., Desai, J. P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Hand+exoskeleton+systems,+clinical+rehabilitation+practices,+and+future+prospects.">Hand exoskeleton systems, clinical rehabilitation practices, and future prospects.</a> IEEE Transactions on Medical Robotics and Bionics. 3 (3), 606-622 (2021).</li><li>Ort, T., Wu, F., Hensel, N. C., Asada, H. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Dynamic+Systems+and+Control+Conference.">Dynamic Systems and Control Conference.</a> , (2023).</li><li>Hussain, I., 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+soft+supernumerary+robotic+finger+and+mobile+arm+support+for+grasping+compensation+and+hemiparetic+upper+limb+rehabilitation.">A soft supernumerary robotic finger and mobile arm support for grasping compensation and hemiparetic upper limb rehabilitation.</a> Robotics and Autonomous Systems. 93, 1-12 (2017).</li><li>Yang, B., Huang, J., Chen, X., Xiong, C., Hasegawa, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Supernumerary+robotic+limbs:+A+review+and+future+outlook.">Supernumerary robotic limbs: A review and future outlook.</a> IEEE Transactions on Medical Robotics and Bionics. 3 (3), 623-639 (2021).</li><li>Tong, Y., Liu, J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Review+of+research+and+development+of+supernumerary+robotic+limbs.">Review of research and development of supernumerary robotic limbs.</a> IEEE/CAA Journal of Automatica Sinica. 8 (5), 929-952 (2021).</li><li>Yap, H. K., 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+magnetic+resonance+compatible+soft+wearable+robotic+glove+for+hand+rehabilitation+and+brain+imaging.">A magnetic resonance compatible soft wearable robotic glove for hand rehabilitation and brain imaging.</a> IEEE Transactions on Neural Systems and Rehabilitation Engineering. 25 (6), 782-793 (2016).</li><li>Yun, S. S., Kang, B. B., Cho, K. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Exo-glove+pm:+An+easily+customizable+modularized+pneumatic+assistive+glove.">Exo-glove pm: An easily customizable modularized pneumatic assistive glove.</a> IEEE Robotics and Automation Letters. 2 (3), 1725-1732 (2017).</li><li>Polygerinos, P., 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=IEEE+International+Workshop+on+Intelligent+Robots+and+Systems+(IROS).">IEEE International Workshop on Intelligent Robots and Systems (IROS).</a> , 1512-1517 (2013).</li><li>Stilli, A., 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=IEEE+International+Conference+on+Soft+Robotics+(RoboSoft).">IEEE International Conference on Soft Robotics (RoboSoft).</a> , 579-584 (2018).</li><li>Zhang, D., 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=Making+sense+of+spatio-temporal+preserving+representations+for+eeg-based+human+intention+recognition.">Making sense of spatio-temporal preserving representations for eeg-based human intention recognition.</a> IEEE Transactions on Cybernetics. 50 (7), 3033-3044 (2019).</li><li>Sirintuna, D., Ozdamar, I., Aydin, Y., Basdogan, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=IEEE+International+Workshop+on+Robot+and+Human+Communication+(ROMAN).">IEEE International Workshop on Robot and Human Communication (ROMAN).</a> , 1280-1287 (2020).</li><li>Mahmud, S., Lin, X., Kim, J. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=2020+10th+Annual+Computing+and+Communincation+Workshop+and+Conferenece+(CCWC).">2020 10th Annual Computing and Communincation Workshop and Conferenece (CCWC).</a> , 0768-0773 (2020).</li><li>Asghar, A., 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=Review+on+electromyography+based+intention+for+upper+limb+control+using+pattern+recognition+for+human-machine+interaction.">Review on electromyography based intention for upper limb control using pattern recognition for human-machine interaction.</a> Proceedings of the Institution of Mechanical Engineers, Part H: Journal of Engineering in Medicine. 236 (5), 628-645 (2022).</li><li>Naghdi, S., Ansari, N. N., Mansouri, K., Hasson, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+neurophysiological+and+clinical+study+of+brunnstrom+recovery+stages+in+the+upper+limb+following+stroke.">A neurophysiological and clinical study of brunnstrom recovery stages in the upper limb following stroke.</a> Brain Injury. 24 (11), 1372-1378 (2010).</li><li>Ru, H., Huang, J., Chen, W., Xiong, C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modeling+and+identification+of+rate-dependent+and+asymmetric+hysteresis+of+soft+bending+pneumatic+actuator+based+on+evolutionary+firefly+algorithm.">Modeling and identification of rate-dependent and asymmetric hysteresis of soft bending pneumatic actuator based on evolutionary firefly algorithm.</a> Mechanism and Machine Theory. 181, 105169 (2023).</li><li>Qin, L., Wu, W., Tian, Y., Xu, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Lidar+filtering+of+urban+areas+with+region+growing+based+on+moving-window+weighted+iterative+least-squares+fitting.">Lidar filtering of urban areas with region growing based on moving-window weighted iterative least-squares fitting.</a> IEEE Geoscience and Remote Sensing Letters. 14 (6), 841-845 (2017).</li><li>Liu, 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=A+two-finger+soft-robotic+gripper+with+enveloping+and+pinching+grasping+modes.">A two-finger soft-robotic gripper with enveloping and pinching grasping modes.</a> IEEE/ASME Transactions on Mechatronics. 26 (1), 146-155 (2020).</li><li>Tawk, C., Sariyildiz, E., Alici, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Force+control+of+a+3D+printed+soft+gripper+with+built-in+pneumatic+touch+sensing+chambers.">Force control of a 3D printed soft gripper with built-in pneumatic touch sensing chambers.</a> Soft Robotics. 9 (5), 970-980 (2022).</li><li>Zuo, W., Song, G., Chen, Z. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Grasping+force+control+of+robotic+gripper+with+high+stiffness.">Grasping force control of robotic gripper with high stiffness.</a> IEEE/ASME Transactions on Mechatronics. 27 (2), 1105-1116 (2021).</li><li>Watanabe, T., Morino, K., Asama, Y., Nishitani, S., Toshima, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Variable-grasping-mode+gripper+with+different+finger+structures+for+grasping+small-sized+items.">Variable-grasping-mode gripper with different finger structures for grasping small-sized items.</a> IEEE Robotics and Automation Letters. 6 (3), 5673-5680 (2021).</li></ol>

The authors have nothing to disclose.

This study presents an innovative, flexible, wearable supernumerary robotic limb designed to assist chronic stroke patients in finger rehabilitation and gripping tasks. This robotic system prioritizes portability and offers both envelope grasp and fingertip grasp functionalities. It incorporates a flexible bending sensor for user-friendly human-machine interaction control. Static grasping experiments validate the gripping capabilities of the designed mechanism in two distinct grasping modes. The study involves experiment...

According to previous research1, as of 2019, there were more than 100 million cases of stroke worldwide. Approximately two-thirds of these cases resulted in hemiplegic sequelae, and over 80% of severe hemiplegic stroke patients could not fully recover hand and arm function2. Furthermore, the aging population is expected to continue growing in the coming decades, leading to a significant increase in the number of potential stroke victims. The persistent upper extremity impairments following a stroke can significantly affect activities of daily living (ADLs), and hand rehabilitation has been clinically recognized as a critical objective for enhancing the activity and participation of chronic stroke patients3.
Traditional motor-driven robotic upper limb devices can provide substantial driving force, but their rigid structures often translate into large sizes and high weights. Moreover, they pose the risk of causing irreversible harm to the human body if they were to malfunction. In contrast, soft pneumatic actuators have demonstrated considerable potential in rehabilitation4, assistance5, and surgical applications6. Their advantages include safety, lightweight construction, and inherent compliance.
In recent years, numerous flexible wearable robots have emerged, designed and developed around soft pneumatic actuators. These robots have been intended for the rehabilitation and post-rehabilitation assistance of stroke patients&#39; upper limbs. They primarily encompass hand exoskeletons7,8, and supernumerary limbs9,10. Although both are used in the fields of wearable robotics and rehabilitation, the former directly interacts with the human body, potentially constraining muscles or joints, while the latter supplements the human workspace or movement without direct constraint11,12. Wearable supernumerary robotic fingers based on servo motors were developed to assist occupational therapists in activities of daily living (ADLs) training9. A similar approach can be found in other research10. These two categories of robotic fingers have introduced novel possibilities for the application of such robots in the rehabilitation assistance of hemiparetic patients. Nonetheless, it is worth noting that the rigid structure employed in these robotic designs may introduce potential considerations regarding user comfort and safety. The design, fabrication, and evaluation of a soft wearable robotic glove were presented13, which can be used for hand rehabilitation and task-specific training during functional Magnetic Resonance Imaging (fMRI). The glove utilizes soft pneumatic actuators made of silicone elastomers to generate finger joint motion, and the device is MR-compatible without causing artifacts in fMRI images. Yun et al. introduced the Exo-Glove PM, a customizable soft pneumatic assistive glove that utilizes an assembly-based approach14. This innovative design features small modules and adjustable distances between them, allowing users to customize the glove based on their phalange length using spacers. This approach maximizes comfort and performance without the need for custom manufacturing. Researchers presented soft actuators composed of elastomeric materials with integrated channels functioning as pneumatic networks15. These actuators generate bending motions that safely conform to human finger movements. Additionally, researchers introduced the AirExGlove, a lightweight and adaptable inflatable soft exoskeleton device16. This system is cost-effective, customizable for different hand sizes, and has successfully accommodated patients with varying levels of muscle spasticity. It offers a more ergonomic and flexible solution compared to rigid-linked robotic systems. While these studies have made significant contributions to the development of flexible wearable hand rehabilitation and assistive robots, it&#39;s worth noting that none of them have achieved complete portability and human-robot interaction control.
Numerous studies have explored the correlation between biological signals, such as electroencephalogram (EEG)17 or electromyogram (EMG) signals18, and human intention. However, both approaches have certain limitations within the constraints of existing devices and technological conditions. Invasive electrodes require surgical procedures on the human body, while non-invasive electrodes suffer from issues such as high noise levels and unreliability in signal acquisition. Detailed discussions of these limitations can be found in the literature19,20. Therefore, the pursuit of research into the portability and user-friendly human-machine interaction capabilities of flexible wearable supernumerary robotic limbs remains highly relevant.
In this study, a unique flexible wearable supernumerary robotic limb was designed and fabricated to assist chronic stroke patients in finger rehabilitation and gripping assistance. This robotic limb is characterized by its lightweight, safety, compliance, waterproofing, and impressive output-to-weight/pressure ratio. Two gripping modes, envelope and fingertip grasping, have been achieved while maintaining portability and ensuring a user-friendly human-robot interaction. The protocol details the design and fabrication process of the pneumatic gripper and the wearable scheme. Additionally, a human-robot interaction method based on flexible bending sensors has been proposed, allowing for convenient and user-friendly control through threshold segmentation. All these aspects have been validated through practical experiments.
The main contributions of this study are summarized as follows: (1) A lightweight, friendly, and wearable flexible supernumerary robotic limb for chronic stroke patients has been designed and fabricated. (2) A reliable method of human-robot interaction has been realized based on flexible bending sensors. (3) Real-world experiments have been conducted to verify the effectiveness and reliability of the proposed mechanism and method, which include output force testing and involve six chronic stroke patients.

<table><tbody><tr><td>Air Compressor</td><td>Xinweicheng</td><td>F35L-JJ-24V</td><td>Provide air supply for the pneumatic gripper</td></tr><tr><td>Arduino&amp;nbsp;</td><td>Emakefun</td><td>Mega 2560</td><td>Single-chip microcomputer/data acquisition card</td></tr><tr><td>Backpack</td><td>Mujin</td><td></td><td>Integrating external devices</td></tr><tr><td>Flex Sensor</td><td>Spectra Symbol</td><td>Flex Sensor 2.2</td><td>Flexible bending sensors</td></tr><tr><td>Power supply</td><td>Yisenneng</td><td>YSN-37019200</td><td>Provide power</td></tr><tr><td>PU quick-plug connector</td><td>Elecall</td><td>PU-6</td><td>Connector for PU tube</td></tr><tr><td>PU tube</td><td>Baishehui</td><td>ZDmJKJJy</td><td>Air line connection</td></tr><tr><td>Silicone elastomer</td><td>Wacker</td><td>ELASTOSIL M4601 A/B</td><td>Material of the pneumatic gripper</td></tr><tr><td>Thermostatic chamber</td><td>Ruyi</td><td>101-00A</td><td>Constant temperature to accelerate the curing of silicone</td></tr><tr><td>Vacuum dryer</td><td>Fujiwara</td><td>PC-3</td><td>Further defoaming</td></tr><tr><td>Vacuum mixing and degassing machine</td><td>Smida</td><td>TMV-200T</td><td>Mix silicone thoroughly and get it defoamed</td></tr><tr><td>Valve</td><td>SMC</td><td>NTV1030-312CL</td><td>Control the air pressure</td></tr></tbody></table>

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.

Output force experiments 
Figure 7 vividly depicts the structural design and dimensions of our actuator, providing a cross-sectional illustration. This actuator comprises two distinct sets of chambers, each containing five elegantly curved air chambers. Remarkably, at the actuator&#39;s terminus, we have ingeniously integrated a protruding structure, reminiscent of an elephant&#39;s trunk tip, significantly expanding the actuator&#39;s gripping radius.
<p class="jov...

Watch this Scientific Journal Video about Enhancing Grasping Abilities for Hemiplegic Patients with Flexible Robotic Limbs at JoVE.com

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.

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 ...

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JoVE Journal

Engineering

2.0K Views.  Huazhong University of Science and Technology. Ons onderzoek richt zich op het ontwikkelen van boventallige robotledematen om hemiplegische patiënten te helpen met grijpbewegingen. Door gebruik te maken van flexibele sensoren willen we de intenties van de patiënt interpreteren en robots in staat stellen verschillende grijptaken uit te voeren, wat uiteindelijk de kwaliteit van leven van de patiënt verbetert. Deze studie introduceert een nieuwe, flexibele, draagbare robotledemaat voor patiënten met een chronische beroerte.Het hel...

Video: Auteur in de schijnwerpers: verbetering van het grijpvermogen voor hemiplegische patiënten met flexibele robotledematen 

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 Robotic Platform to Study the Foreflipper of the California Sea Lion

The California sea lion (Zalophus californianus), is an agile and powerful swimmer. Unlike many successful swimmers (dolphins, tuna), they generate most of their thrust with their large foreflippers. This protocol describes a robotic platform designed to study the hydrodynamic performance of the swimming California sea lion (Zalophus californianus). The robot is a model of the animal&#39;s foreflipper that is actuated by motors to replicate the motion of its propulsive stroke (the &#39;clap&#39;). The kinematics of the sea lion&#39;s propulsive stroke are extracted from video data of unmarked, non-research sea lions at the Smithsonian Zoological Park (SNZ). Those data form the basis of the actuation motion of the robotic flipper presented here. The geometry of the robotic flipper is based a on high-resolution laser scan of a foreflipper of an adult female sea lion, scaled to about 60% of the full-scale flipper. The articulated model has three joints, mimicking the elbow, wrist and knuckle joint of the sea lion foreflipper. The robotic platform matches dynamics properties&#8212;Reynolds number and tip speed&#8212;of the animal when accelerating from rest. The robotic flipper can be used to determine the performance (forces and torques) and resulting flowfields.

A robotic platform is described that will be used to study the hydrodynamic performance&#8212;forces and flowfields&#8212;of the swimming California sea lion. The robot is a model of the animal&#39;s foreflipper that is actuated by motors to replicate the motion of its propulsive stroke (the &#39;clap&#39;).

The California sea lion (Zalophus californianus), is an agile and powerful swimmer. Unlike many successful swimmers (dolphins, tuna), they generate most ...

Scalable Solution-processed Fabrication Strategy for High-performance, Flexible, Transparent Electrodes with Embedded Metal Mesh

Here, the authors report the embedded metal-mesh transparent electrode (EMTE), a new transparent electrode (TE) with a metal mesh completely embedded in a polymer film. This paper also presents a low-cost, vacuum-free fabrication method for this novel TE; the approach combines lithography, electroplating, and imprint transfer (LEIT) processing. The embedded nature of the EMTEs offers many advantages, such as high surface smoothness, which is essential for organic electronic device production; superior mechanical stability during bending; favorable resistance to chemicals and moisture; and strong adhesion with plastic film. LEIT fabrication features an electroplating process for vacuum-free metal deposition and is favorable for industrial mass production. Furthermore, LEIT allows for the fabrication of metal mesh with a high aspect ratio (i.e., thickness to linewidth), significantly enhancing its electrical conductance without adversely losing optical transmittance. We demonstrate several prototypes of flexible EMTEs, with sheet resistances lower than 1 &#937;/sq and transmittances greater than 90%, resulting in very high figures of merit (FoM) &#8211; up to 1.5 x 104 &#8211; which are amongst the best values in the published literature.

This protocol describes a solution-based fabrication strategy for high-performance, flexible, transparent electrodes with fully-embedded, thick metal mesh. Flexible transparent electrodes fabricated by this process demonstrate among the highest reported performances, including ultra-low sheet resistance, high optical transmittance, mechanical stability under bending, strong substrate adhesion, surface smoothness, and environmental stability.

Here, the authors report the embedded metal-mesh transparent electrode (EMTE), a new transparent electrode (TE) with a metal mesh completely embedded in a ...

A Fabrication and Measurement Method for a Flexible Ferroelectric Element Based on Van Der Waals Heteroepitaxy

Flexible non-volatile memories have received much attention as they are applicable for portable smart electronic device in the future, relying on high-density data storage and low-power consumption capabilities. However, the high-quality oxide based nonvolatile memory on flexible substrates is often constrained by the material characteristics and the inevitable high-temperature fabrication process. In this paper, a protocol is proposed to directly grow an epitaxial yet flexible lead zirconium titanate memory element on muscovite mica. The versatile deposition technique and measurement method enable the fabrication of flexible yet single-crystalline non-volatile memory elements necessary for the next generation of smart devices.

In this paper, we present a protocol to directly grow an epitaxial yet flexible lead zirconium titanate memory element on muscovite mica.

Flexible non-volatile memories have received much attention as they are applicable for portable smart electronic device in the future, relying on ...

Isokinetic Robotic Device to Improve Test-Retest and Inter-Rater Reliability for Stretch Reflex Measurements in Stroke Patients with Spasticity

Measuring spasticity is important in treatment planning and determining efficacy after treatment. However, the current tool used in clinical settings has been shown to be limited in inter-rater reliability. One factor in this poor inter-rater reliability is the variability of passive motion while measuring the angle of catch (AoC) measurements. Therefore, an isokinetic device has been proposed to standardize the manual joint motion; however, the benefits of isokinetic motion for AoC measurements has not been tested in a standardized manner. This protocol investigates whether isokinetic motion itself can improve inter-rater reliability for AoC measurements. For this purpose, a robotic isokinetic device was developed that is combined with surface electromyography (EMG). Two conditions, manual and isokinetic motions, are compared with the standardized method to measure the angle and subjective feeling of catch. It is shown that in 17 stroke patients with mild elbow flexor spasticity, isokinetic motion improved the intraclass correlation coefficient (ICC) for inter-rater reliability of AoC measurements to 0.890 [95% confidence interval (CI): 0.685&#8211;0.961] by the EMG criteria, and 0.931 (95% CI: 0.791&#8211;0.978) by the torque criteria, from 0.788 (95% CI: 0.493&#8211;0.920) by manual motion. In conclusion, isokinetic motion itself can improve inter-rater reliability of AoC measurements in stroke patients with mild spasticity. Given that this system may provide greater standardized angle measurements and catch of feeling, it may be a good option for the evaluation of spasticity in a clinical setting.

Using a robotic isokinetic device with electromyography (EMG) measurements, this protocol illustrates that isokinetic motion itself can improve inter-rater reliability for the angle of catch measurements in stroke patients with mild elbow flexor spasticity.

Measuring spasticity is important in treatment planning and determining efficacy after treatment. However, the current tool used in clinical settings has ...

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

Use of a Foot-Induced Digitally Controlled Resistance Device for Functional Magnetic Resonance Imaging Evaluation in Patients with Foot Paresis

Neurological deficits from a stroke can result in long-term motor disabilities, including those that affect walking gait. However, extensive rehabilitation following stroke is typically time limited. Establishing predictive biomarkers to identify patients who may meaningfully benefit from additional physical therapy and demonstrate improvement is important to improve the patients&#39; quality of life. Detection of neuroplastic remodeling of the affected region and changes in the activity patterns excited while performing suitable motor tasks could have valuable implications for chronic stroke recovery. This protocol describes the use of a digitally controlled, magnetic resonance-compatible foot-induced robotic device (MR_COFID) to present a personalized foot-motor task involving trajectory following to stroke-affected subjects with gait impairment during functional magnetic resonance imaging (fMRI). In the task, foot flexion is performed against bi-directional resistive forces, which are tuned to the subject&#39;s strength in both the dorsiflexion and plantar flexion directions, while following a visual metronome. fMRI non-invasively uses endogenous deoxyhemoglobin as a contrast agent to detect blood oxygenation level-dependent (BOLD) changes between the active and resting periods during testing. Repeated periodic testing can detect therapy-related changes in excitation patterns during task performance. The use of this technique provides data to identify and measure biomarkers that may indicate the likelihood of an individual benefitting from rehabilitation beyond that which is currently provided to stroke patients.

Chronic stroke patients' insured rehabilitation is generally time limited. Imaging-based study of brain activity from walking-related motor tasks can lead to establishing biomarkers to measure improved outcomes and justify extending tailored therapy. A novel, magnetic resonance-compatible, variable-resistance foot motion device and a protocol for use during functional magnetic resonance imaging are presented.

Neurological deficits from a stroke can result in long-term motor disabilities, including those that affect walking gait. However, extensive ...

Neuroscience

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 ...

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 ...

A Flexible Wearable Supernumerary Robotic Limb for Chronic Stroke Patients

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