{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,7]],"date-time":"2026-02-07T13:39:10Z","timestamp":1770471550873,"version":"3.49.0"},"reference-count":57,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T00:00:00Z","timestamp":1763337600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Hand rehabilitation requires consistent, repetitive exercises that can often reduce patient motivation, especially in home-based therapy. This study introduces ReHAb Playground, a deep learning-based system that merges real-time gesture recognition with 3D hand tracking to create an engaging and adaptable rehabilitation experience built in the Unity Game Engine. The system utilizes a YOLOv10n model for hand gesture classification and MediaPipe Hands for 3D hand landmark extraction. Three mini-games were developed to target specific motor and cognitive functions: Cube Grab, Coin Collection, and Simon Says. Key gameplay parameters, namely repetitions, time limits, and gestures, can be tuned according to therapeutic protocols. Experiments with healthy participants were conducted to establish reference performance ranges based on average completion times and standard deviations. The results showed a consistent decrease in both task completion and gesture times across trials, indicating learning effects and improved control of gesture-based interactions. The most pronounced improvement was observed in the more complex Coin Collection task, confirming the system\u2019s ability to support skill acquisition and engagement in rehabilitation-oriented activities. ReHAb Playground was conceived with modularity and scalability at its core, enabling the seamless integration of additional exercises, gesture libraries, and adaptive difficulty mechanisms. While preliminary, the findings highlight its promise as an accessible, low-cost rehabilitation platform suitable for home use, capable of monitoring motor progress over time and enhancing patient adherence through engaging, game-based interactions. Future developments will focus on clinical validation with patient populations and the implementation of adaptive feedback strategies to further personalize the rehabilitation process.<\/jats:p>","DOI":"10.3390\/fi17110522","type":"journal-article","created":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T08:50:07Z","timestamp":1763542207000},"page":"522","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["ReHAb Playground: A DL-Based Framework for Game-Based Hand Rehabilitation"],"prefix":"10.3390","volume":"17","author":[{"given":"Samuele","family":"Rasetto","sequence":"first","affiliation":[{"name":"Biomedical Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2359-4409","authenticated-orcid":false,"given":"Giorgia","family":"Marullo","sequence":"additional","affiliation":[{"name":"Management and Production Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]},{"given":"Ludovica","family":"Adamo","sequence":"additional","affiliation":[{"name":"Biomedical Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]},{"given":"Federico","family":"Bordin","sequence":"additional","affiliation":[{"name":"Biomedical Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-5070-1423","authenticated-orcid":false,"given":"Francesca","family":"Pavesi","sequence":"additional","affiliation":[{"name":"Biomedical Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7839-6218","authenticated-orcid":false,"given":"Chiara","family":"Innocente","sequence":"additional","affiliation":[{"name":"Management and Production Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]},{"given":"Enrico","family":"Vezzetti","sequence":"additional","affiliation":[{"name":"Management and Production Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8407-0660","authenticated-orcid":false,"given":"Luca","family":"Ulrich","sequence":"additional","affiliation":[{"name":"Management and Production Engineering, Politecnico di Torino, C.so Duca degli Abruzzi, 24, 10129 Torino, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2025,11,17]]},"reference":[{"key":"ref_1","unstructured":"Ning, H., Wang, Z., Li, R., Zhang, Y., and Mao, L. (2022). A review on serious games for exercise rehabilitation. arXiv."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Tomi\u0107, T.J.D., Savi\u0107, A.M., Vidakovi\u0107, A.S., Rodi\u0107, S.Z., Isakovi\u0107, M.S., Rodr\u00edguez-de Pablo, C., Keller, T., and Konstantinovi\u0107, L.M. (2017). ArmAssist robotic system versus matched conventional therapy for poststroke upper limb rehabilitation: A randomized clinical trial. BioMed Res. Int., 2017.","DOI":"10.1155\/2017\/7659893"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1161\/CIR.0b013e318282ab8f","article-title":"Heart disease and stroke statistics\u20142013 update: A report from the American Heart Association","volume":"127","author":"Go","year":"2013","journal-title":"Circulation"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Norouzi-Gheidari, N., Levin, M.F., Fung, J., and Archambault, P. (2013, January 26\u201329). Interactive virtual reality game-based rehabilitation for stroke patients. Proceedings of the 2013 International Conference on Virtual Rehabilitation (ICVR), Piscataway, NJ, USA.","DOI":"10.1109\/ICVR.2013.6662126"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13063-017-1815-9","article-title":"Electrical somatosensory stimulation followed by motor training of the paretic upper limb in acute stroke: Study protocol for a randomized controlled trial","volume":"18","author":"Ghaziani","year":"2017","journal-title":"Trials"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1007\/s00371-009-0387-4","article-title":"Optimising engagement for stroke rehabilitation using serious games","volume":"25","author":"Burke","year":"2009","journal-title":"Vis. Comput."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"358152","DOI":"10.1155\/2014\/358152","article-title":"An overview of serious games","volume":"2014","author":"Laamarti","year":"2014","journal-title":"Int. J. Comput. Games Technol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1080\/17483107.2017.1290702","article-title":"Serious games for upper limb rehabilitation: A systematic review","volume":"13","author":"Quaresma","year":"2018","journal-title":"Disabil. Rehabil. Assist. Technol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1186\/s12984-021-00889-1","article-title":"Serious games for upper limb rehabilitation after stroke: A meta-analysis","volume":"18","author":"Doumas","year":"2021","journal-title":"J. Neuroeng. Rehabil."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Marullo, G., Innocente, C., Ulrich, L., Lo Faro, A., Porcelli, A., Ruggieri, R., Vecchio, B., and Vezzetti, E. (2025). Home-based mirror therapy in phantom limb pain treatment: The augmented humans framework. Multimedia Tools and Applications, Springer.","DOI":"10.1007\/s11042-025-20628-1"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"8339","DOI":"10.1109\/ACCESS.2022.3140434","article-title":"The impact of problem-based serious games on learning motivation","volume":"10","author":"Moradi","year":"2022","journal-title":"IEEE Access"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Ulrich, L., Carmassi, G., Garelli, P., Lo Presti, G., Ramondetti, G., Marullo, G., Innocente, C., and Vezzetti, E. (2024). SIGNIFY: Leveraging machine learning and gesture recognition for sign language teaching through a serious game. Future Internet, 16.","DOI":"10.3390\/fi16120447"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Corona, F., Chiuri, R.M., Filocamo, G., Fo\u00e0, M., Lanzi, P.L., Lopopolo, A., and Petaccia, A. (2018, January 15\u201317). Serious games for wrist rehabilitation in juvenile idiopathic arthritis. Proceedings of the 2018 IEEE Games, Entertainment, Media Conference (GEM), Galway, Ireland.","DOI":"10.1109\/GEM.2018.8516458"},{"key":"ref_14","unstructured":"Ao, W., Hui, C., Lihao, L., Chen, A., Lin, Z., Han, J., and Ding, G. (2024). YOLOv10: Real-Time End-to-End Object Detection. arXiv."},{"key":"ref_15","unstructured":"Zhang, F., Bazarevsky, V., Vakunov, A., Tkachenka, A., Sung, G., Chang, C.L., and Grundmann, M. (2020). Mediapipe hands: On-device real-time hand tracking. arXiv."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Pereira, M.F., Prahm, C., Kolbenschlag, J., Oliveira, E., and Rodrigues, N.F. (2020, January 12\u201314). A virtual reality serious game for hand rehabilitation therapy. Proceedings of the 2020 IEEE 8th International Conference on Serious Games and Applications for Health (SeGAH), Vancouver, BC, Canada.","DOI":"10.1109\/SeGAH49190.2020.9201789"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Song, X., Ali, N.M., Mhd Salim, M.H., and Rezaldi, M.Y. (2025). A literature review of virtual reality exergames for older adults: Enhancing physical, cognitive, and social health. Appl. Sci., 15.","DOI":"10.3390\/app15010351"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Dore, B., Gaudreault, A., Everard, G., Ayena, J.C., Abboud, A., Robitaille, N., and Batcho, C.S. (2023). Acceptability, feasibility, and effectiveness of immersive virtual technologies to promote exercise in older adults: A systematic review and meta-analysis. Sensors, 23.","DOI":"10.3390\/s23052506"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"e54193","DOI":"10.2196\/54193","article-title":"A Virtual Reality Serious Game for the Rehabilitation of Hand and Finger Function: Iterative Development and Suitability Study","volume":"12","author":"Bressler","year":"2024","journal-title":"JMIR Serious Games"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.cmpb.2017.08.008","article-title":"Motion Rehab AVE 3D: A VR-based exergame for post-stroke rehabilitation","volume":"151","author":"Trombetta","year":"2017","journal-title":"Comput. Methods Programs Biomed."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1111\/jgs.12624","article-title":"Comparing the energy expenditure of Wii-Fit-based therapy with that of traditional physiotherapy in an older adult population","volume":"62","author":"Taylor","year":"2014","journal-title":"J. Am. Geriatr. Soc."},{"key":"ref_22","unstructured":"Fiorin, M.R., De Marchi, A.C.B., Colussi, E.L., Rieder, R., and Trombetta, M. (2014, January 19\u201322). Motion Rehab: Um jogo s\u00e9rio para idosos com sequelas de Acidente Vascular Encef\u00e1lico. Proceedings of the XIV Simp\u00f3sio Brasileiro de Computa\u00e7\u00e3o Aplicada \u00e0 Sa\u00fade (SBCAS), Foz do Igua\u00e7u, Brazil."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Elnaggar, A., and Reichardt, D. (2016, January 15\u201317). Digitizing the hand rehabilitation using serious games methodology with user-centered design approach. Proceedings of the 2016 International Conference on Computational Science and Computational Intelligence (CSCI), Las Vegas, NV, USA.","DOI":"10.1109\/CSCI.2016.0011"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Yan, S., Xiong, Y., and Lin, D. (2018, January 2\u20137). Spatial temporal graph convolutional networks for skeleton-based action recognition. Proceedings of the AAAI Conference on Artificial Intelligence, New Orleans, LO, USA.","DOI":"10.1609\/aaai.v32i1.12328"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"2433","DOI":"10.1007\/s00371-020-01955-w","article-title":"Sta-gcn: Two-stream graph convolutional network with spatial\u2013temporal attention for hand gesture recognition","volume":"36","author":"Zhang","year":"2020","journal-title":"Vis. Comput."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Chen, J., Zhao, S., Meng, H., Cheng, X., and Tan, W. (2022). An interactive game for rehabilitation based on real-time hand gesture recognition. Front. Physiol., 13.","DOI":"10.3389\/fphys.2022.1028907"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Husna, R., Brata, K.C., Anggraini, I.T., Funabiki, N., Rahmadani, A.A., and Fan, C.P. (2025). An Investigation of Hand Gestures for Controlling Video Games in a Rehabilitation Exergame System. Computers, 14.","DOI":"10.3390\/computers14010025"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Xiao, Y., Funabiki, N., Anggraini, I.T., Shih, C.L., and Fan, C.P. (2024). A Study of Exergame System Using Hand Gestures for Wrist Flexibility Improvement for Tenosynovitis Prevention. Information, 15.","DOI":"10.3390\/info15100622"},{"key":"ref_29","unstructured":"Schoorl, K., Cisneros, T.P., Salah, A.A., and Schouten, B. (2024). Wrist movement classification for adaptive mobile phone based rehabilitation of children with motor skill impairments. arXiv."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1007\/s10055-025-01124-1","article-title":"Augmented reality for upper limb rehabilitation: Real-time kinematic feedback with HoloLens 2","volume":"29","author":"Luciani","year":"2025","journal-title":"Virtual Real."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S0268-0033(99)00058-3","article-title":"Contribution of the extrinsic and intrinsic hand muscles to the moments in finger joints","volume":"15","author":"Li","year":"2000","journal-title":"Clin. Biomech."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Akba\u015f, A. (2025). Hand-Focused Strength and Proprioceptive Training for Improving Grip Strength and Manual Dexterity in Healthy Adults: A Systematic Review and Meta-Analysis. J. Clin. Med., 14.","DOI":"10.3390\/jcm14196882"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"394","DOI":"10.1016\/0003-9993(94)90161-9","article-title":"Recovery of upper extremity function in stroke patients: The Copenhagen Stroke Study","volume":"75","author":"Nakayama","year":"1994","journal-title":"Arch. Phys. Med. Rehabil."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.jht.2017.01.004","article-title":"Hand strengthening exercises in chronic stroke patients: Dose-response evaluation using electromyography","volume":"31","author":"Vinstrup","year":"2018","journal-title":"J. Hand Ther."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"745","DOI":"10.1161\/STROKEAHA.109.572065","article-title":"Presence of finger extension and shoulder abduction within 72 hours after stroke predicts functional recovery: Early prediction of functional outcome after stroke: The EPOS cohort study","volume":"41","author":"Nijland","year":"2010","journal-title":"Stroke"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Kim, D., Baghi, R., Koh, K., and Zhang, L.Q. (2023). MCP extensors respond faster than flexors in individuals with severe-to-moderate stroke-caused impairment: Evidence of uncoupled neural pathways. Front. Neurol., 14.","DOI":"10.3389\/fneur.2023.1119761"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Jarque-Bou, N.J., Vergara, M., and Sancho-Bru, J.L. (2024). Understanding forearm muscle activity during everyday common grasps: Insights for rehabilitation, prosthetic control, and human\u2013machine interaction. Appl. Sci., 14.","DOI":"10.3390\/app14083190"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"580","DOI":"10.1016\/j.jht.2022.07.003","article-title":"Movement preferences of the wrist and forearm during activities of daily living","volume":"36","author":"Anderton","year":"2023","journal-title":"J. Hand Ther."},{"key":"ref_39","unstructured":"Alif, M.A.R., and Hussain, M. (2024). YOLOv1 to YOLOv10: A comprehensive review of YOLO variants and their application in the agricultural domain. arXiv."},{"key":"ref_40","first-page":"107984","article-title":"Yolov10: Real-time end-to-end object detection","volume":"37","author":"Wang","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Mao, M., Lee, A., and Hong, M. (2024). Efficient Fabric Classification and Object Detection Using YOLOv10. Electronics, 13.","DOI":"10.3390\/electronics13193840"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Kwon, O.J., Kim, J., Lee, J., and Ullah, F. (2025). Evaluation of Benchmark Datasets and Deep Learning Models with Pre-Trained Weights for Vision-Based Dynamic Hand Gesture Recognition. Appl. Sci., 15.","DOI":"10.3390\/app15116045"},{"key":"ref_43","unstructured":"Bazarevsky, V., and Zhang, F. (2019). On-Device, Real-Time Hand Tracking with Mediapipe, Google AI Blog."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Reimer, D., Podkosova, I., Scherzer, D., and Kaufmann, H. (2023). Evaluation and improvement of HMD-based and RGB-based hand tracking solutions in VR. Front. Virtual Real., 4.","DOI":"10.3389\/frvir.2023.1169313"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Pu, M., Chong, C.Y., and Lim, M.K. (2023, January 14). Robustness evaluation in hand pose estimation models using metamorphic testing. Proceedings of the 2023 IEEE\/ACM 8th International Workshop on Metamorphic Testing (MET), Melbourne, Australia.","DOI":"10.1109\/MET59151.2023.00012"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Maggioni, V., Azevedo-Coste, C., Durand, S., and Bailly, F. (2025). Optimisation and comparison of markerless and marker-based motion capture methods for hand and finger movement analysis. Sensors, 25.","DOI":"10.3390\/s25041079"},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Amprimo, G., Masi, G., Pettiti, G., Olmo, G., Priano, L., and Ferraris, C. (2024). Hand tracking for clinical applications: Validation of the Google MediaPipe Hand (GMH) and the depth-enhanced GMH-D frameworks. Biomed. Signal Process. Control, 96.","DOI":"10.1016\/j.bspc.2024.106508"},{"key":"ref_48","unstructured":"Bazarevsky, V., Grishchenko, I., Raveendran, K., Zhu, T., Zhang, F., and Grundmann, M. (2020). Blazepose: On-device real-time body pose tracking. arXiv."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"172","DOI":"10.1109\/TPAMI.2019.2929257","article-title":"Openpose: Realtime multi-person 2d pose estimation using part affinity fields","volume":"43","author":"Cao","year":"2019","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_50","unstructured":"Intel (2024). Intel RealSense Viewer Home Page, Intel."},{"key":"ref_51","unstructured":"Intel (2024). Intel RealSense Depth Camera SR300 Series Product Family Datasheet, Intel."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"577","DOI":"10.1080\/10447318.2018.1455307","article-title":"The System Usability Scale: Past, Present, and Future","volume":"34","author":"Lewis","year":"2018","journal-title":"Int. J. Hum.\u2013Comput. Interact."},{"key":"ref_53","unstructured":"Brooke, J. (1996). SUS: A \u2019Quick and Dirty\u2019 Usability Scale. Usability Evaluation In Industry, CRC Press."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Sauro, J., and Lewis, J.R. (2012). Quantifying the User Experience: Practical Statistics for User Research, Morgan Kaufmann Publishers Inc.. [1st ed.].","DOI":"10.1016\/B978-0-12-384968-7.00002-3"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.ijhcs.2018.01.004","article-title":"A practical approach to measuring user engagement with the refined user engagement scale (UES) and new UES short form","volume":"112","author":"Cairns","year":"2018","journal-title":"Int. J. Hum.-Comput. Stud."},{"key":"ref_56","unstructured":"Sabat\u00e9, E. (2003). Adherence to Long-Term Therapies: Evidence for Action, World Health Organization."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1051","DOI":"10.1136\/bmj.321.7268.1051","article-title":"Qualitative analysis of stroke patients\u2019 motivation for rehabilitation","volume":"321","author":"Maclean","year":"2000","journal-title":"Bmj"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/17\/11\/522\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,19]],"date-time":"2025-11-19T09:05:18Z","timestamp":1763543118000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/17\/11\/522"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,17]]},"references-count":57,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2025,11]]}},"alternative-id":["fi17110522"],"URL":"https:\/\/doi.org\/10.3390\/fi17110522","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,11,17]]}}}