A Novel Soft Glove for Hand Tremor Suppression: Evaluation of Layer Jamming Actuator Placement
Abstract
The following paper presents the concept of a layer jamming based soft glove for hand tremor suppression, its implementation, validation of the soft glove for hand tremor suppression and evaluation of the effect of layer jamming actuator placement. Wearable tremor suppression devices can avoid the side effects which occur due to available medical treatments, but contemporary methods are bulky and negatively affects the voluntary motions of the hand. Hence, a soft tremor suppression device can be developed to overcome the issues faced in contemporary wearable devices. A hand tremor suppression device using layer jamming was proposed in the study. In this study, experimentation for the material selection for layer jamming elements, evaluation of the layer jamming element placement and validation of the soft glove were conducted to characterize and evaluate the performance of the soft glove. Layer jamming material selection was done by measuring the deflection against an applied load. The performance of the soft glove was evaluated by measuring the suppression of a simulated tremor for the dorsal and palmar configurations. Performance evaluation shows a maximum tremor reduction of 78.32% in the palmar side element configuration in comparison to 38.23% in the dorsal side. Performance evaluation shows promising results in the suppression of hand tremors using the proposed soft glove and the results suggest that the palmar side element configuration can achieve higher tremor reduction comparatively.
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The jamming-actuator soft glove yielded an amplitude reduction of 74.79 ± 4.23% for the palmar-side actuator placement.
“The maximum tremor reduction was obtained for the placement of the actuator in the palmar side, and it yielded to an amplitude reduction of 74.79 ± 4.23%.”
From A Review on Wearable Technologies for Tremor Suppression (2021) · cites this paper as [62]
Cites
Soft robotics: a bioinspired evolution in robotics
Kim, S., Laschi, C., & Trimmer, B. (2013) · Trends in Biotechnology · doi:10.1016/j.tibtech.2013.03.002 · Cited by 2,092 · see citing works
Bhatia, K. P., Bain, P., Bajaj, N., Elble, R. J., Hallett, M., Louis, E. D., Raethjen, J., Stamelou, M., Testa, C. M., Deuschl, G., et al. (2018) · Movement Disorders · doi:10.1002/mds.27121 · Cited by 1,575 · see citing works
The challenges ahead for bio-inspired 'soft' robotics
Pfeifer, R., Lungarella, M., & Fumiya Iida, A. (2012) · Communications of the ACM · doi:10.1145/2366316.2366335 · Cited by 383 · see citing works
Design and Validation of a Rehabilitation Robotic Exoskeleton for Tremor Assessment and Suppression
Rocon, E., Belda-Lois, J. M., Ruiz, A. F., Manto, M., Moreno, J. C., & Pons, J. L. (2007) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2007.903917 · Cited by 349 · cited 1× · see citing works
“tremor assessment and suppression (WOTAS) focuses on the suppression of tremors in the forearm and wrist and do not suppress hand tremors in fingers [14].”
BackgroundMechanically Versatile Soft Machines through Laminar Jamming
Narang, Y., Vlassak, J. J., & Howe, R. D. (2018) · Advanced Functional Materials · doi:10.1002/adfm.201707136 · Cited by 258 · see citing works
Soft robotic glove for hand rehabilitation and task specific training
Polygerinos, P., Galloway, K. C., Savage, E., Herman, M., Donnell, K. O., & Walsh, C. J. (2015) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2015.7139597 · Cited by 250 · see citing works
Carmignano, S. M. (2003) · IMPERIAL COLLEGE PRESS eBooks · doi:10.1142/9781860949364_0015 · Cited by 187 · see citing works
Morrison, B. M. (2016) · Seminars in Neurology · doi:10.1055/s-0036-1586263 · Cited by 102 · see citing works
Zubrycki, I., & Granosik, G. (2016) · Journal of Intelligent & Robotic Systems · doi:10.1007/s10846-016-0392-6 · Cited by 68 · see citing works
Wang, L., Nurzaman, S. G., & Iida, F. (2017) · Foundations and Trends in Robotics · doi:10.1561/2300000055 · Cited by 62 · see citing works
Development of a Wearable Tremor Suppression Glove
Zhou, Y., Jenkins, M. E., Naish, M. D., & Trejos, A. L. (2018) · IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob) · doi:10.1109/biorob.2018.8487197 · Cited by 60 · see citing works
Fromme, N. P., Camenzind, M., Riener, R., & Rossi, R. (2019) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-019-0543-7 · Cited by 56 · see citing works
Soft Fingers with Controllable Compliance to Enable Realization of Low Cost Grippers
Lin, K.-Y., & Gupta, S. K. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-63537-8_48 · Cited by 10 · see citing works
Taking on Essential Tremor: New Tools and Approaches Offer patients Increased Treatment Options
Mertz, L. (2016) · IEEE Pulse · doi:10.1109/mpul.2016.2538481 · Cited by 7 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Soft Sensors and Actuators for Wearable Human–Machine Interfaces
Park, J., Lee, Y., Cho, S., Choe, A., Yeom, J., Ro, Y. G., Kim, J., Kang, D., Lee, S., & Ko, H. (2024) · Chemical Reviews · doi:10.1021/acs.chemrev.3c00356 · Cited by 287 · see citing works
A Review on Wearable Technologies for Tremor Suppression
Lora-Millan, J. S., Delgado-Oleas, G., Benito-León, J., & Rocon, E. (2021) · Frontiers in Neurology · doi:10.3389/fneur.2021.700600 · Cited by 62 · see citing works
“actuator (62) Joint rigidity controlled by”
BackgroundFazio, R. D., Mastronardi, V., Petruzzi, M., Vittorio, M. D., & Visconti, P. (2022) · Future Internet · doi:10.3390/fi15010014 · Cited by 55 · see citing works
“According to us, the sensing approach based on inertial sensors, implemented in [110] and [125], is the most promising in terms of un-obtrusiveness, accuracy, and integrability in wearable devices.”
BackgroundMethodSoft Gloves: A Review on Recent Developments in Actuation, Sensing, Control and Applications
Tiboni, M., & Amici, C. (2022) · Actuators · doi:10.3390/act11080232 · Cited by 38 · see citing works
4D printing of soft orthoses for tremor suppression
Mohammadi, M., Zolfagharian, A., Bodaghi, M., Xiang, Y., & Kouzani, A. Z. (2022) · Bio-Design and Manufacturing · doi:10.1007/s42242-022-00199-y · Cited by 37 · see citing works
“Recently developed laminar soft actuators have been utilized in hand tremor suppressors due to their ability to mitigate hand tremors both in the wrist [52] and fingers [53].”
BackgroundInfluentialDesign and Preliminary Performance Assessment of a Wearable Tremor Suppression Glove
Zhou, Y., Ibrahim, A. H., Hardy, K. G., Jenkins, M. E., Naish, M. D., & Trejos, A. L. (2021) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2021.3080622 · Cited by 33 · see citing works
Robotic Systems for Hand Rehabilitation—Past, Present and Future
Gherman, B. G., Zima, I., Vaida, C. L., Tucan, P., Pîslă, A., Bîrlescu, I., Machado, J., & Pisla, D. L. (2025) · Technologies · doi:10.3390/technologies13010037 · Cited by 30 · see citing works
A Layer Jamming Soft Glove for Hand Tremor Suppression
Wanasinghe, A. T., Awantha, W. V. I., Kavindya, A. G. P., Kulasekera, A. L., Chathuranga, D. S., & Senanayake, B. (2021) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2021.3135497 · Cited by 22 · see citing works
Self-citationKulasekera, A. L., Arumathanthri, R. B., Chathuranga, D. S., Gopura, R. A. R. C., & Lalitharatne, T. D. (2021) · Sensors and Actuators A Physical · doi:10.1016/j.sna.2021.113088 · Cited by 17 · see citing works
Self-citationTowards Essential Hand Tremor Suppression via Pneumatic Artificial Muscles
Skaramagkas, V., Andrikopoulos, G., & Manesis, S. A. (2021) · Actuators · doi:10.3390/act10090206 · Cited by 14 · see citing works
Analysis of the Effect of Common Disturbances on the Safety of a Wearable Tremor Suppression Device
Zhou, Y., Ibrahim, A. H., Jenkins, M. E., Naish, M. D., & Trejos, A. L. (2021) · IEEE Robotics and Automation Letters · doi:10.1109/lra.2021.3062592 · Cited by 13 · see citing works
Soft Robotics for Parkinson’s Disease Supported by Functional Materials and Artificial Intelligence
Mazumdar, H., Khondakar, K. R., Das, S., & Kaushik, A. K. (2025) · BME Frontiers · doi:10.34133/bmef.0143 · Cited by 12 · see citing works
Design and Development of a Novel Bio-inspired Worm-type Soft Robot for In-pipe Locomotion
Dewapura, J. I., Hemachandra, P. S., Dananjaya, T., Awantha, W. V. I., Wanasinghe, A. T., Kulasekera, A. L., Chathuranga, D. S., & Dassanayake, V. P. C. (2020) · International Conference on Control, Automation and Systems (ICCAS) · doi:10.23919/iccas50221.2020.9268402 · Cited by 12 · see citing works
“Therefore, these robots could be used in instances where the use of a conventional robot may be impossible and are currently being used in developing a range of robots including bionic devices such as orthoses or in industrial applications such as grippers and robot arms [3][4][5].”
BackgroundSelf-citationArleo, L., Bondì, G., Albini, S., Maselli, M., & Cianchetti, M. (2021) · Engineering Research Express · doi:10.1088/2631-8695/ac1fc6 · Cited by 10 · see citing works
Shagan, A., Chase-Markopoulou, C., Walter, J. R., Sellhorn-Timm, J., Shao, Y., Nadler, T., Benson, A., Wochner, I., Rumley, E. H., Wurster, I., et al. (2025) · Device · doi:10.1016/j.device.2025.100719 · Cited by 7 · see citing works
Zhou, Y., Daemi, P., Jenkins, M. E., Naish, M. D., & Trejos, A. L. (2024) · IEEE Transactions on Medical Robotics and Bionics · doi:10.1109/tmrb.2024.3350769 · Cited by 6 · see citing works
“A WTSD suppresses tremor by delivering either motion and force to the user’s joint(s) [6], [7], [8], [9], [10], [11], [12], [13] or by stimulating muscles via electrical stimulation [6], [14], [15], [16], [17], [18].”
BackgroundEvaluation of Hand Tremor Frequency Among Patients in Sri Lanka using a Soft Glove
Kavindya, P., Awantha, W. V. I., Wanasinghe, A. T., Kulasekera, A. L., Chathuranga, D. S., & Senanayake, B. (2020) · Moratuwa Engineering Research Conference (MERCon) · doi:10.1109/mercon50084.2020.9185382 · Cited by 7 · see citing works
“Therefore, as part of an ongoing research towards developing a soft orthotic device for the suppression of hand tremors, measurements of hand tremors of patients in Sri Lanka were needed to be taken [5].”
BackgroundSelf-citationA Review of Techniques Used to Suppress Tremor
Saleh, S. K., Mohammed, S. L., & Al-Askery, A. J. (2022) · Journal of Techniques · doi:10.51173/jt.v4i4.774 · Cited by 6 · see citing works
Yousef, M., Hafizh, M., Sassi, S., & Muthalif, A. G. A. (2023) · Journal of Vibration and Control · doi:10.1177/10775463231158196 · Cited by 4 · see citing works
“Active tremor suppression often utilizes feedback systems that actively inhibit the vibrations using electrical stimulation on the muscles responsible for the motion (Awantha et al., 2020; Zhang et al., 2019; Zhou et al., 2021b).”
BackgroundTowards a Modular Pathological Tremor Simulation System Based on the Stewart Platform
Fajardo, J., & de Melo, L. F. (2023) · Sensors · doi:10.3390/s23229020 · Cited by 4 · see citing works
Advanced non-linear control based on artificial intelligence tuner for hand tremor suppression
Faraji, B., Rouhollahi, K., Nezhadi, A., & Jamalpoor, Z. (2023) · Transactions of the Institute of Measurement and Control · doi:10.1177/01423312221148769 · Cited by 4 · see citing works
“In recent years, researchers have been interested in wearable gadgets such as GyroGlove and wearable Glove (WG) as a temporary approach for controlling hand tremor (Awantha et al., 2020; Faizan and Muzammil, 2020).”
BackgroundLayer Jammers in a Simulated Environment Soft Haptic (S.E.S.H.) Glove
Levy, B., Doshi, M. V., Lin, K.-Y., & Wehner, M. F. (2024) · IEEE Haptics Symposium · doi:10.1109/haptics59260.2024.10520848 · Cited by 2 · see citing works
“There has been work with soft robotic gloves for virtual reality medical applications [21], and teleoperation [22].”
BackgroundTamás, E., Földi, S., Makk, Á., & Cserey, G. (2025) · Frontiers in Robotics and AI · doi:10.3389/frobt.2025.1537470 · Cited by 2 · see citing works
Zhou, Y., Jenkins, M. E., Naish, M. D., & Trejos, A. L. (2022) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc48229.2022.9871546 · Cited by 1 · see citing works
Investigation and development of hand tremor controlling device
Saleh, S. K., Mohammed, S. L., Al-Askery, A. J., & Jameel, H. F. (2023) · AIP conference proceedings · doi:10.1063/5.0155773 · Cited by 1 · see citing works
Mechatronic Devices for Upper Limb Tremor
Zhou, Y., Daemi, P., Edmonds, B. P. R., Habibollahi, Z., Jenkins, M. E., Naish, M. D., & Trejos, A. L. (2023) · Contemporary clinical neuroscience · doi:10.1007/978-3-031-26128-2_22 · Cited by 1 · see citing works
A Feedback-Controlled Jamming Approach for Variable-Stiffness Actuators in Untethered Soft Robots
Allen, J., Bagci, F. S., Kim, K. A., Hofmann, M. K., & Dorsey, K. L. (2025) · IEEE International Conference on Soft Robotics (RoboSoft) · doi:10.1109/robosoft63089.2025.11020902 · Cited by 1 · see citing works
“In jamming actuators, the stiffness tuning is typically achieved by evacuating the actuator to compress particles [8], [15], [16], layers [3], [10], [17], or fibers [11], [18], [19].”
InfluentialMulti-parameter Model for Layer Jamming Element Performance for Use in Robotic Applications
Awantha, W. V. I., Kulasekera, A. L., & Chathuranga, D. S. (2021) · International Conference on Information and Automation for Sustainability (ICIAfS) · doi:10.1109/iciafs52090.2021.9606151
Self-citationFajardo, J., & de Melo, L. F. (2023) · Brazilian Journal of Health Review · doi:10.34119/bjhrv6n4-252
Viscous damping of tremor using a wearable robot with an optimized mechanical metamaterial
Kulkarni, S. R., Accoto, D., & Campolo, D. (2024) · Wearable Technologies · doi:10.1017/wtc.2024.15
A Wearable Hand Tremor-Suppressing Glove Using PVC Gel-Based Actuators and Force Sensors
Liu, C., Wang, Y., & Zhang, K.-T. (2026) · IEEE/ASME transactions on mechatronics · doi:10.1109/tmech.2026.3663307
- Authors
- Awantha, W. V. I., Wanasinghe, A. T., Kavindya, A. G. P., Kulasekera, A. L., & Chathuranga, D. S.
- Affiliations
- University of Moratuwa (LK)
- Venue
- 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft)
- Publisher
- IEEE
- Published
- 2020-05
- Pages
- 440-445
- OpenAlex
- W3035977414
- Cited by
- 31
- References
- 14
- Citations by year
- 2026: 1 · 2025: 5 · 2024: 4 · 2023: 6 · 2022: 5 · 2021: 8 · 2020: 2
- FWCI
- 9.53
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE International Conference on Soft Robotics (RoboSoft) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Soft Robotics and Applications
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Physical Sciences › Engineering › Mechanical Engineering › Advanced Materials and Mechanics
- Keywords
- layer jamming, wearable devices, actuator placement, tremor suppression, soft robotics, material selection
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