17.1.3.5.9 Rehabilitation Systems, Rehabilitation Techniques

Sekhavat, Y.A., Namani, M.S.,
Projection-Based AR: Effective Visual Feedback in Gait Rehabilitation,
HMS(48), No. 6, December 2018, pp. 626-636.
IEEE DOI 1812
augmented reality, cognition, feedback, gait analysis, kinematics, patient rehabilitation, projection-based AR, gait rehabilitation, visual feedback BibRef

Rechy-Ramirez, E.J.[Ericka Janet], Marin-Hernandez, A.[Antonio], Rios-Figueroa, H.V.[Homero Vladimir],
A human-computer interface for wrist rehabilitation: A pilot study using commercial sensors to detect wrist movements,
VC(35), No. 1, January 2018, pp. 41-55.
Springer DOI
WWW Link. 1902
BibRef

Liu, Z.[Zhong], Wang, X.[Xin'an], Su, M.L.[Ming-Liang], Le, L.[Leon],
Research on rehabilitation training bed with action prediction based on NARX neural network,
IJIST(29), No. 4, 2019, pp. 539-546.
DOI Link 1911
action prediction, electromyography signal, NARX, recurrent neural network, rehabilitation training BibRef

Zhang, Y.J.[Yu-Jing], Lu, X.[Xu],
Measurement method for human body anteflexion angle based on image processing,
IJIST(29), No. 4, 2019, pp. 518-530.
DOI Link 1911
adaptive Gaussian filter, angle of the human body, edge detection, feature point extraction, gradient magnitude BibRef

Miura, S., Yokoo, Y., Nakashima, Y., Ogaya, Y., Nihei, M., Ando, T., Kobayashi, Y., Fujie, M.G.,
Determination of the Gain for a Walking Speed Amplifying Belt Using Brain Activity,
HMS(50), No. 2, April 2020, pp. 154-164.
IEEE DOI 2004
Ergonomics, gait recognition, human-computer interaction, human-robot interaction BibRef

Ferreira, B.[Bruno], Ferreira, P.M.[Pedro M.], Pinheiro, G.[Gil], Figueiredo, N.[Nelson], Carvalho, F.[Filipe], Menezes, P.[Paulo], Batista, J.[Jorge],
Deep learning approaches for workout repetition counting and validation,
PRL(151), 2021, pp. 259-266.
Elsevier DOI 2110
BibRef
Earlier:
Exploring Workout Repetition Counting and Validation Through Deep Learning,
ICIAR20(I:3-15).
Springer DOI 2007
Workout repetition counting, Human physical activity analysis, 2D Human pose estimation, Deep learning BibRef

Garcia-Rodriguez, J.[Jose], Gomez-Donoso, F.[Francisco], Oprea, S.[Sergiu], Garcia-Garcia, A.[Alberto], Cazorla, M.[Miguel], Orts-Escolano, S.[Sergio], Bauer, Z.[Zuria], Castro-Vargas, J.[John], Escalona, F.[Felix], Ivorra-Piqueres, D.[David], Martinez-Gonzalez, P.[Pablo], Aguirre, E.[Eugenio], Garcia-Silviente, M.[Miguel], Garcia-Perez, M.[Marcelo], Cañas, J.M.[Jose M.], Martin-Rico, F.[Francisco], Gines, J.[Jonathan], Rivas-Montero, F.[Francisco],
COMBAHO: A deep learning system for integrating brain injury patients in society,
PRL(137), 2020, pp. 80-90.
Elsevier DOI 2008
Robot assistants, Ambient assisted living, Rehabilitation aids BibRef

Ito, T.[Takahide], Nakamura, Y.[Yuichi], Kondo, K.[Kazuaki], Knoop, E.[Espen], Rossiter, J.[Jonathan],
Design and Performance Analysis of a Skin-Stretcher Device for Urging Head Rotation,
IEICE(E103-D), No. 11, November 2020, pp. 2314-2322.
WWW Link. 2011
BibRef

Akiyama, Y., Kushida, R., Okamoto, S., Yamada, Y.,
Characteristics of Recovery Motion Resulting From Side Contact With a Physical Assistant Robot Worn During Gait,
HMS(50), No. 6, December 2020, pp. 518-528.
IEEE DOI 2011
Legged locomotion, Collision mitigation, Motion analysis, Assistive technology, Wearable computers, Collision, fall risk, reaction motion BibRef

Bouton, C.,
Brain Implants and Wearables Reroute Signals to Restore Movement and Sensation,
Spectrum(58), No. 2, February 2021, pp. 28-33.
IEEE DOI 2102
Presses, Wearable computers, Games, Neural implants, Bars BibRef

Chen, J.H.[Jia-Hao], Qiao, H.[Hong],
Muscle-Synergies-Based Neuromuscular Control for Motion Learning and Generalization of a Musculoskeletal System,
SMCS(51), No. 6, June 2021, pp. 3993-4006.
IEEE DOI 2106
Mathematical model, Robots, Computational modeling, Control systems, Neuromuscular, Motion generalization, neuromuscular control BibRef

Mengüç, E.C.[Engin Cemal], Çinar, S.[Salim], Xiang, M.[Min], Mandic, D.P.[Danilo P.],
Online Censoring Based Weighted-Frequency Fourier Linear Combiner for Estimation of Pathological Hand Tremors,
SPLetters(28), 2021, pp. 1460-1464.
IEEE DOI 2108
Frequency measurement, Real-time systems, Pathology, Estimation, Signal processing algorithms, Indexes, Weight measurement, wearable and assistive technology BibRef

Xu, W.[Wei], Xiang, D.H.[Dong-Hai], Wang, G.[Guotai], Liao, R.[Ruisong], Shao, M.[Ming], Li, K.[Kang],
Multiview Video-Based 3-D Pose Estimation of Patients in Computer-Assisted Rehabilitation Environment (CAREN),
HMS(52), No. 2, April 2022, pp. 196-206.
IEEE DOI 2203
Heating systems, Training, Pose estimation, Kernel, Videos, Hospitals, Deep learning, orthopedic patients BibRef

Rivas, J.J.[Jesús Joel], del Carmen-Lara, M.[María], Castrejón, L.[Luis], Hernández-Franco, J.[Jorge], Orihuela-Espina, F.[Felipe], Palafox, L.[Lorena], Williams, A.[Amanda], Bianchi-Berthouze, N.[Nadia], Sucar, L.E.[Luis Enrique],
Multi-Label and Multimodal Classifier for Affective States Recognition in Virtual Rehabilitation,
AffCom(13), No. 3, July 2022, pp. 1183-1194.
IEEE DOI 2209
Pain, Bayes methods, Computational modeling, Videos, Integrated optics, Face recognition, Convergence, Affective states, virtual rehabilitation BibRef

Thomas, B.[Brennan], Lu, M.L.[Ming-Lun], Jha, R.[Rashmi], Bertrand, J.[Joseph],
Machine Learning for Detection and Risk Assessment of Lifting Action,
HMS(52), No. 6, December 2022, pp. 1196-1204.
IEEE DOI 2212
Lifting equipment, Sensors, Wearable computers, Data models, Safety, Risk management, Employee welfare, Signal detection, wearable systems BibRef

Goyal, T.[Tanishka], Hussain, S.[Shahid], Martinez-Marroquin, E.[Elisa], Brown, N.A.T.[Nicholas A. T.], Jamwal, P.K.[Prashant K.],
Stiffness-Observer-Based Adaptive Control of an Intrinsically Compliant Parallel Wrist Rehabilitation Robot,
HMS(53), No. 1, February 2023, pp. 65-74.
IEEE DOI 2301
Wrist, Actuators, End effectors, Muscles, Robots, Robot kinematics, Prototypes, Biomimetic muscle actuators (BMAs), wrist stiffness model BibRef

Sabater, A.[Alberto], Montesano, L.[Luis], Murillo, A.C.[Ana C.],
Event Transformer^+. A Multi-Purpose Solution for Efficient Event Data Processing,
PAMI(45), No. 12, December 2023, pp. 16013-16020.
IEEE DOI 2311
BibRef
Earlier:
Event Transformer. A sparse-aware solution for efficient event data processing,
ECV22(2676-2685)
IEEE DOI 2210
Power demand, Graphics processing units, Gesture recognition, Benchmark testing, Transformers, Data processing BibRef

Sabater, A.[Alberto], Santos, L.[Laura], Santos-Victor, J.[José], Bernardino, A.[Alexandre], Montesano, L.[Luis], Murillo, A.C.[Ana C.],
One-shot action recognition in challenging therapy scenarios,
LLID21(2771-2779)
IEEE DOI 2109
Target recognition, Dynamics, Medical treatment, Kinematics, Pattern recognition, Noise measurement BibRef

Liu, Z.[Zemin], Ai, Q.S.[Qing-Song], Liu, H.J.[Hao-Jie], Meng, W.[Wei], Liu, Q.[Quan],
Human-Like Trajectory Planning Based on Postural Synergistic Kernelized Movement Primitives for Robot-Assisted Rehabilitation,
HMS(54), No. 2, April 2024, pp. 152-161.
IEEE DOI 2404
Trajectory, Robots, Task analysis, Trajectory planning, Robot kinematics, Principal component analysis, Motors, trajectory planning BibRef

Abedi, A.[Ali], Bisht, P.[Paritosh], Chatterjee, R.[Riddhi], Agrawal, R.[Rachit], Sharma, V.[Vyom], Jayagopi, D.B.[Dinesh Babu], Khan, S.S.[Shehroz S.],
Rehabilitation Exercise Repetition Segmentation and Counting Using Skeletal Body Joints,
CRV23(288-295)
IEEE DOI 2406
Analytical models, Privacy, Data privacy, Computational modeling, Neural networks, Patient rehabilitation, exercise segmentation, virtual rehabilitation BibRef

Ahn, S.[Sihu], Jo, Y.W.[Yong-Won], Park, J.[Jinhyeok], Kim, S.[Sangmin], Kim, J.[Jungin], Kim, S.B.[Seoung Bum], Lee, M.G.[Min-Goo], Lee, S.[Sangmin], Kim, Y.[Younghoon],
Multimodal Human Action Recognition for Rehabilitation Exercise of Upper Body for Individuals With Cerebral Palsy,
SMCS(54), No. 7, July 2024, pp. 4164-4174.
IEEE DOI 2406
Skeleton, Data models, Computational modeling, Human activity recognition, Cybernetics, Current measurement, upper body rehabilitation exercise BibRef

Kryeem, A.[Alaa], Raz, S.[Shmuel], Eluz, D.[Dana], Itah, D.[Dorit], Hel-Or, H.[Hagit], Shimshoni, I.[Ilan],
Personalized Monitoring in Home Healthcare: An Assistive System for Post Hip Replacement Rehabilitation,
ACVR23(1860-1869)
IEEE DOI 2401
BibRef

Zhao, Z.[Ziyi], Kiciroglu, S.[Sena], Vinzant, H.[Hugues], Cheng, Y.[Yuan], Katircioglu, I.[Isinsu], Salzmann, M.[Mathieu], Fua, P.[Pascal],
3d Pose Based Feedback for Physical Exercises,
ACCV22(IV:189-205).
Springer DOI 2307
BibRef

Kanade, A.[Aditya], Sharma, M.[Mansi], Muniyandi, M.[Manivannan],
Tele-evalnet: A Low-cost, Teleconsultation System for Home Based Rehabilitation of Stroke Survivors Using Multiscale CNN-convlstm Architecture,
ACVR22(738-750).
Springer DOI 2304
BibRef

Réby, K.[Kévin], Dulau, I.[Idriss], Dubrasquet, G.[Guillaume], Aimar, M.B.[Marie Beurton],
Graph Transformer for Physical Rehabilitation Evaluation,
FG23(1-8)
IEEE DOI 2303
Patient monitoring, Medical specialties, Predictive models, Transformers, Skeleton, Motion capture, Behavioral sciences BibRef

Sun, Y.[Yaowei], Li, G.[Gang], Zhao, T.Z.[Tong-Zhou],
Research on Lightweight Network of Human Posture Estimation for Physical Training,
ICRVC22(62-67)
IEEE DOI 2301
Training, Computational modeling, Robot kinematics, Pose estimation, Real-time systems, Mobile handsets BibRef

Bai, X.T.[Xiang-Tian], Ma, J.[Jun], Dai, D.[Duan],
The Wearable Resistance Exercise Booster's Design for the Elderly,
DHM21(I:81-91).
Springer DOI 2108
BibRef

Cotton, R.J.,
Kinematic Tracking of Rehabilitation Patients With Markerless Pose Estimation Fused with Wearable Inertial Sensors,
FG20(508-514)
IEEE DOI 2102
gait analysis, handicapped aids, image motion analysis, injuries, kinematics, neurophysiology, patient rehabilitation, markerless pose estimation BibRef

Gu, Y., Pandit, S., Saraee, E., Nordahl, T., Ellis, T., Betke, M.,
Home-Based Physical Therapy with an Interactive Computer Vision System,
ACVR19(2619-2628)
IEEE DOI 2004
diseases, interactive systems, learning (artificial intelligence), medical computing, deep learning models BibRef

Dahms, R.[Rebecca], Stamm, O.[Oskar], Müller-Werdan, U.[Ursula],
Developing a VR Training Program for Geriatric Patients with Chronic Back Pain,
VAMR19(II:243-255).
Springer DOI 1909
BibRef

Alex, M., Chen, C., Wünsche, B.C.,
A review of sensor devices in stroke rehabilitation,
IVCNZ17(1-6)
IEEE DOI 1902
body sensor networks, computer games, patient rehabilitation, patient treatment, rehabilitation outcomes, sensor technologies BibRef

Armas, J.[Joseph], Andaluz, V.H.[Víctor H.],
Alternative Treatment of Psychological Disorders Such as Spider Phobia Through Virtual Reality Environments,
ISVC18(687-697).
Springer DOI 1811
BibRef

Galarza, E.E.[Eddie E.], Pilatasig, M.[Marco], Galarza, E.D.[Eddie D.], López, V.M.[Victoria M.], Zambrano, P.A.[Pablo A.], Buele, J.[Jorge], Espinoza, J.[Jhon],
Virtual Reality System for Children Lower Limb Strengthening with the Use of Electromyographic Sensors,
ISVC18(215-225).
Springer DOI 1811
BibRef

Ilyas, C.M.A., Nasrollahi, K., Rehm, M., Moeslund, T.B.,
Rehabilitation of Traumatic Brain Injured Patients: Patient Mood Analysis from Multimodal Video,
ICIP18(2291-2295)
IEEE DOI 1809
Face, Databases, Brain injuries, Face recognition, Feature extraction, Machine learning, Cameras BibRef

Liu, L.[Lu], Dong, Z.X.[Zhan-Xun], Tang, N.[Ning],
An Interactive Training System Design for Ankle Rehabilitation,
DHM18(169-182).
Springer DOI 1807
BibRef

Nagaya, S.[Sachiko], Hayashi, H.[Hisae],
The Effect of Ankle Exercise on Cerebral Blood Oxygenation During and After Postural Change,
DHM18(183-192).
Springer DOI 1807
BibRef

Kim, G.[Gyoung], Biocca, F.[Frank],
Immersion in Virtual Reality Can Increase Exercise Motivation and Physical Performance,
VAMR18(II: 94-102).
Springer DOI 1807
BibRef

Guryanov, R.A., Monkin, S., Monkin, A., Petrov, A.,
Approach to 3D Analysis of Gravity Ptosis,
PTVSBB17(123-127).
DOI Link 1805
BibRef

Bonenfant, M., Laurendeau, D., Fortin-Côté, A., Cardou, P., Gosselin, C., Faure, C., McFadyen, B., Mercier, C., Bouyer, L.,
A Computer Vision System for Virtual Rehabilitation,
CRV17(269-276)
IEEE DOI 1804
image motion analysis, image sensors, medical image processing, patient rehabilitation, virtual reality BibRef

Baharum, A.[Aslina], Yusop, N.M.M.[Nurhafizah Moziyana Mohd], Ramli, R.Z.[Ratna Zuarni], Fabeil, N.F.[Noor Fazlinda], Amirul, S.M.[Sharifah Milda], Halamy, S.[Suhaida],
Utilizing Mobile Application for Reducing Stress Level,
IVIC17(489-499).
Springer DOI 1711
BibRef

Omar, M.Y.[Mohd Yusoff], Rambli, D.R.A.[Dayang Rohaya Awang], Shiratuddin, M.F.[Mohd Fairuz],
Designing Persuasive Stroke Rehabilitation Game: An Analysis of Persuasion Context,
IVIC17(559-569).
Springer DOI 1711
BibRef

Dhamija, S., Boult, T.E.,
Learning Visual Engagement for Trauma Recovery,
Assist18(84-93)
IEEE DOI 1806
BibRef
Earlier:
Exploring Contextual Engagement for Trauma Recovery,
DeepAffective17(2267-2277)
IEEE DOI 1709
behavioural sciences computing, emotion recognition, face recognition, human factors, Visualization. Context modeling, Facial features, Machine learning, Mood, Predictive models, Videos BibRef

Dittmar, C.[Cornelia], Denzler, J.[Joachim], Gross, H.M.[Horst-Michael],
A Feedback Estimation Approach for Therapeutic Facial Training,
FG17(141-148)
IEEE DOI 1707
Estimation, Face, Facial features, Feature extraction, Medical treatment, Training BibRef

Andaluz, V.H.[Víctor H.], Salazar, P.J.[Pablo J.], Escudero V., M.[Miguel], Bustamante D., C.[Carlos], Quevedo, W.[Washington], Sánchez, J.S.[Jorge S.], Espinosa, E.G.[Edison G.], Rivas, D.[David],
Virtual Reality Integration with Force Feedback in Upper Limb Rehabilitation,
ISVC16(II: 259-268).
Springer DOI 1701
BibRef

Antunes, M.[Michel], Baptista, R.[Renato], Demisse, G.[Girum], Aouada, D.[Djamila], Ottersten, B.[Björn],
Visual and Human-Interpretable Feedback for Assisting Physical Activity,
ACVR16(II: 115-129).
Springer DOI 1611
BibRef

Carrier-Baudouin, T.[Tristan], Chapdelaine, C.[Claude], Lalonde, M.[Marc], Quinn, P.[Philippe], Foucher, S.[Samuel],
Solving Rendering Issues in Realistic 3D Immersion for Visual Rehabilitation,
ACVR16(II: 223-237).
Springer DOI 1611
BibRef

Busam, B., Esposito, M., Frisch, B., Navab, N.,
Quaternionic Upsampling: Hyperspherical Techniques for 6 DoF Pose Tracking,
3DV16(629-638)
IEEE DOI 1701
computer vision BibRef

Busam, B., Esposito, M., Che'Rose, S., Navab, N., Frisch, B.,
A Stereo Vision Approach for Cooperative Robotic Movement Therapy,
ACVR15(519-527)
IEEE DOI 1602
Cameras BibRef

Palma, C.[Carlos], Salazar, A.[Augusto], Vargas, F.[Francisco],
HMM Based Evaluation of Physical Therapy Movements Using Kinect Tracking,
ISVC15(I: 174-183).
Springer DOI 1601
BibRef

Patil, Y.[Yogendra], Brandão, I.[Iara], Siqueira, G.[Guilherme], Hu, F.[Fei],
Home Oriented Virtual e-Rehabilitation,
ISVC15(II: 586-596).
Springer DOI 1601
BibRef

Hoermann, S., Collins, J., Regenbrecht, H.,
Learning from rehabilitation: A bi-manual interface approach,
3DUI15(163-164)
IEEE DOI 1511
augmented reality BibRef

Ye, M.X.[Min-Xiang], Yang, C.[Cheng], Stankovic, V.[Vladimir], Stankovic, L.[Lina], Kerr, A.[Andrew],
Kinematics Analysis Multimedia System for Rehabilitation,
QoEM15(571-579).
Springer DOI 1511
BibRef

Babruwad, S.[Sujay], Avaghan, R.[Rahul], Mudenagudi, U.[Uma],
A Mobile Augmented Reality Framework for Post-stroke Patient Rehabilitation,
IMEV14(396-406).
Springer DOI 1504
BibRef

Matthew, R.P.[Robert Peter], Kurillo, G.[Gregorij], Han, J.J.[Jay J.], Bajcsy, R.[Ruzena],
Calculating Reachable Workspace Volume for Use in Quantitative Medicine,
ACVR14(570-583).
Springer DOI 1504
Where a person can reach, evaluation of disease, etc. BibRef

Cantu, M., Espinoza, E., Guo, R.[Rongkai], Quarles, J.,
Game cane: An assistive 3DUI for rehabilitation games,
3DUI14(43-46)
IEEE DOI 1406
computer games BibRef

Avola, D.[Danilo], Cinque, L.[Luigi], Levialdi, S.[Stefano], Petracca, A.[Andrea], Placidi, G.[Giuseppe], Spezialetti, M.[Matteo],
Time-of-Flight Camera Based Virtual Reality Interaction for Balance Rehabilitation Purposes,
CompIMAGE14(363-374).
Springer DOI 1407
BibRef

Shin, Y.[Yoonyong], Wunsche, B.C.,
A smartphone-based golf simulation exercise game for supporting arthritis patients,
IVCNZ13(459-464)
IEEE DOI 1402
Global Positioning System BibRef

Robertson, C., Vink, L., Regenbrecht, H., Lutteroth, C., Wunsche, B.C.,
Mixed reality Kinect Mirror box for stroke rehabilitation,
IVCNZ13(231-235)
IEEE DOI 1402
augmented reality BibRef

Venkataraman, V.[Vinay], Vlachos, I.[Ioannis], Turaga, P.K.[Pavan K.],
Dynamical Regularity for Action Analysis,
BMVC15(xx-yy).
DOI Link 1601
BibRef

Venkataraman, V.[Vinay], Turaga, P.K.[Pavan K.], Lehrer, N.[Nicole], Baran, M.[Michael], Rikakis, T.[Thanassis], Wolf, S.L.[Steven L.],
Attractor-Shape for Dynamical Analysis of Human Movement: Applications in Stroke Rehabilitation and Action Recognition,
HAU3D13(514-520)
IEEE DOI 1309
Action Recognition BibRef

Li, J.[Jian], Li, H.[Hui], Zhang, X.F.[Xiu-Feng], Pan, G.X.[Guo-Xin], Xiao, Q.J.[Qi-Jun],
The design and implementation of lower limb rehabilitation robot based on BWSTT,
ICARCV12(1558-1562).
IEEE DOI 1304
BibRef

Dukes, P.S., Hayes, A., Hodges, L.F., Woodbury, M.,
Punching ducks for post-stroke neurorehabilitation: System design and initial exploratory feasibility study,
3DUI13(47-54)
IEEE DOI 1406
avatars BibRef

Bozgeyikli, E., Bozgeyikli, L., Clevenger, M., Raij, A., Alqasemi, R., Dubey, R.,
Design and development of a virtual reality system for vocational rehabilitation of individuals with disabilities,
3DUI14(175-176)
IEEE DOI 1406
computer based training BibRef

d'Amico, G.[Gianpaolo], Landucci, L.[Lea], Pezzatini, D.[Daniele],
Natural Interactive System for Hemispatial Neglect Rehabilitation,
SBA13(501-508).
Springer DOI 1309
Tools for improving rehab systems. BibRef

Cordella, F.[Francesca], di Corato, F.[Francesco], Zollo, L.[Loredana], Siciliano, B.[Bruno],
A Robust Hand Pose Estimation Algorithm for Hand Rehabilitation,
ACVR13(1-10).
Springer DOI 1309
BibRef

da Gama, A.[Alana], Chaves, T.[Thiago], Figueiredo, L.[Lucas], Teichrieb, V.[Veronica],
Improving motor rehabilitation process through a natural interaction based system using Kinect sensor,
3DUI12(145-146).
IEEE DOI 1204
BibRef

Gil-Jiménez, P.[Pedro], Losilla-López, B.[Beatriz], Torres-Cueco, R.[Rafael], Campilho, A.[Aurélio], López-Sastre, R.J.[Roberto J.],
Hand Detection and Tracking Using the Skeleton of the Blob for Medical Rehabilitation Applications,
ICIAR12(II: 130-137).
Springer DOI 1206
BibRef

Franchi, D.[Danilo], Maurizi, A.[Alfredo], Placidi, G.[Giuseppe],
Characterization of a SimMechanics Model for a Virtual Glove Rehabilitation System,
CompIMAGE10(141-150).
Springer DOI 1006
Track rehab efforts. BibRef

Chapter on Motion -- Human Motion, Surveillance, Tracking, Surveillance, Activities continues in
Rehabilitation Systems, Prosthesis Systems, Control .

Last update:Sep 28, 2024 at 17:47:54