17.1.3.5.9 Rehabilitation Systems, Rehabilitation Techniques

Chapter Contents (Back)
Rehabilitation. Therapy.
See also Human Safety, Drowning, Underwater, Home Care, Smart Home.
See also Rehabilitation Systems, Prosthesis Systems, Control.

Nguyen, V.H.[Van-Hanh], Merienne, F.[Frederic], Martinez, J.L.[Jean-Luc],
Training Based On Real-time Motion Evaluation For Functional Rehabilitation In Virtual Environment,
IJIG(10), No. 2, April 2010, pp. 235-250.
DOI Link 1003
BibRef

Nguyen, V.H.[Van-Hanh], Merienne, F.[Frederic], Martinez, J.L.[Jean-Luc],
An Efficient Approach for Human Motion Data Mining Based on Curves Matching,
ICCVG10(I: 163-184).
Springer DOI 1009
BibRef

Ferrari, A.,
Technical innovations for the diagnosis and the rehabilitation of motor and perceptive impairments of the child with Cerebral Palsy,
Ph.D.Thesis, University of Bologna, 2010.
PDF File. 1109
BibRef

Huete, A.J., Victores, J.G., Martinez, S., Gimenez, A., Balaguer, C.,
Personal Autonomy Rehabilitation in Home Environments by a Portable Assistive Robot,
SMC-C(42), No. 4, July 2012, pp. 561-570.
IEEE DOI 1206
BibRef

Liu, Y.J.[Yong-Jiu], Song, Q.J.[Quan-Jun], Wang, B.[Buyun], Liu, Y.Y.[Yan-Yang], Nie, Y.M.[Yu-Man], Wang, H.[Hui], Shuang, F.[Feng],
Design of A Novel Gait Simulator for Rehabilitation Training,
Sensors(150), No. 2, March 2013, pp. 90-96.
HTML Version. 1304
BibRef

Regenbrecht, H., Hoermann, S., Ott, C., Muller, L., Franz, E.,
Manipulating the Experience of Reality for Rehabilitation Applications,
PIEEE(102), No. 2, February 2014, pp. 170-184.
IEEE DOI 1403
augmented reality BibRef

Raheja, J.L.[Jagdish L.], Chaudhary, A.[Ankit], Nandhini, K., Maiti, S.,
Pre-consultation help necessity detection based on gait recognition,
SIViP(9), No. 6, September 2015, pp. 1357-1363.
Springer DOI 1509
BibRef

Lai, C.L.[Chung-Liang], Tseng, C.M.[Chien-Ming], Erdenetsogt, D., Liao, T.K.[Tzu-Kuan], Huang, Y.L.[Ya-Ling], Chen, Y.F.[Yung-Fu],
A Kinect-Based System for Balance Rehabilitation of Stroke Patients,
IEICE(E99-D), No. 4, April 2016, pp. 1032-1037.
WWW Link. 1604
BibRef

Wang, W.Q.[Wei-Qun], Hou, Z.G.[Zeng-Guang], Cheng, L.[Long], Tong, L.[Lina], Peng, L.[Liang], Peng, L.[Long], Tan, M.[Min],
Toward Patients-' Motion Intention Recognition: Dynamics Modeling and Identification of iLeg: An LLRR Under Motion Constraints,
SMCS(46), No. 7, July 2016, pp. 980-992.
IEEE DOI 1606
Dynamics BibRef

Stirling, L., MacLean, J.,
Roadmap for the Development of at-Home Telemonitoring Systems to Augment Occupational Therapy,
HMS(46), No. 4, August 2016, pp. 569-580.
IEEE DOI 1608
cognition BibRef

Novak, D.[Domen], Riener, R.[Robert],
Control Strategies and Artificial Intelligence in Rehabilitation Robotics,
AIMag(36), No. 4, Winter 2015, pp. 23-33.
WWW Link. 1609
BibRef

Zhang, F., Hou, Z.G., Cheng, L., Wang, W., Chen, Y., Hu, J., Peng, L., Wang, H.,
iLeg: A Lower Limb Rehabilitation Robot: A Proof of Concept,
HMS(46), No. 5, October 2016, pp. 761-768.
IEEE DOI 1610
PI control BibRef

Gomez-Donoso, F.[Francisco], Orts-Escolano, S.[Sergio], Garcia-Garcia, A.[Alberto], Garcia-Rodriguez, J.[Jose], Castro-Vargas, J.A.[John Alejandro], Ovidiu-Oprea, S.[Sergiu], Cazorla, M.[Miguel],
A robotic platform for customized and interactive rehabilitation of persons with disabilities,
PRL(99), No. 1, 2017, pp. 105-113.
Elsevier DOI 1710
BibRef

Niyetkaliyev, A.S., Hussain, S., Ghayesh, M.H., Alici, G.,
Review on Design and Control Aspects of Robotic Shoulder Rehabilitation Orthoses,
HMS(47), No. 6, December 2017, pp. 1134-1145.
IEEE DOI 1712
DC motors, Exoskeletons, Manipulators, Medical treatment, Orthopedic procedures, Patient rehabilitation, Shoulder, Actuation, stroke BibRef

Kurita, Y., Sato, J., Tanaka, T., Shinohara, M., Tsuji, T.,
Unpowered Sensorimotor-Enhancing Suit Reduces Muscle Activation and Improves Force Perception,
HMS(47), No. 6, December 2017, pp. 1158-1163.
IEEE DOI 1712
Breast, Clothing, Electromyography, Fabrics, Force, Muscles, Shoulder, Force reproduction, sensorimotor performance, unpowered assistive clothing BibRef

Hamaya, M.[Masashi], Matsubara, T.[Takamitsu], Noda, T.[Tomoyuki], Teramae, T.[Tatsuya], Morimoto, J.[Jun],
Learning assistive strategies for exoskeleton robots from user-robot physical interaction,
PRL(99), No. 1, 2017, pp. 67-76.
Elsevier DOI 1710
Exoskeleton robot BibRef

Erdogan, H.[Huseyin], Palaska, Y.[Yunus], Masazade, E.[Engin], Barkana, D.E.[Duygun Erol], Ekenel, H.K.[Hazim Kemal],
Vision-based game design and assessment for physical exercise in a robot-assisted rehabilitation system,
IET-CV(12), No. 1, February 2018, pp. 59-68.
DOI Link 1801
BibRef

Tao, L.[Lili], Burghardt, T.[Tilo], Mirmehdi, M.[Majid], Damen, D.[Dima], Cooper, A.[Ashley], Camplani, M.[Massimo], Hannuna, S.[Sion], Paiement, A.[Adeline], Craddock, I.[Ian],
Energy expenditure estimation using visual and inertial sensors,
IET-CV(12), No. 1, February 2018, pp. 36-47.
DOI Link 1801
BibRef

Ma, R., Hu, F.,
An Intelligent Thermal Sensing System for Automatic, Quantitative Assessment of Motion Training in Lower-Limb Rehabilitation,
SMCS(48), No. 5, May 2018, pp. 661-669.
IEEE DOI 1804
Cameras, Foot, Legged locomotion, Motion segmentation, Sensors, Skeleton, Training, Motion segmentation, physical therapy, thermal camera BibRef

Wu, Q., Wang, X., Chen, B., Wu, H.,
Development of a Minimal-Intervention-Based Admittance Control Strategy for Upper Extremity Rehabilitation Exoskeleton,
SMCS(48), No. 6, 2018, pp. 1005-1016.
IEEE DOI 1805
Exoskeletons, Extremities, Medical treatment, Real-time systems, Robots, Training, Trajectory, Admittance control strategy, upper extremity exoskeleton BibRef

Capecci, M.[Marianna], Ciabattoni, L.[Lucio], Ferracuti, F.[Francesco], Monteriù, A.[Andrea], Romeo, L.[Luca], Verdini, F.[Federica],
Collaborative design of a telerehabilitation system enabling virtual second opinion based on fuzzy logic,
IET-CV(12), No. 4, June 2018, pp. 502-512.
DOI Link 1805
BibRef

Watanabe, T.[Takashi], Tadano, T.[Takumi],
Experimental Tests of a Prototype of IMU-Based Closed-Loop Fuzzy Control System for Mobile FES Cycling with Pedaling Wheelchair,
IEICE(E101-D), No. 7, July 2018, pp. 1906-1914.
WWW Link. 1807
FES: functional electrical stimulation. BibRef

Eichler, N.[Nadav], Hel-Or, H.[Hagit], Shimshoni, I.[Ilan], Itah, D.[Dorit], Gross, B.[Bella], Raz, S.[Shmuel],
3D motion capture system for assessing patient motion during Fugl-Meyer stroke rehabilitation testing,
IET-CV(12), No. 7, October 2018, pp. 963-975.
DOI Link 1809
BibRef

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

Brahmi, B., Saad, M., Rahman, M.H., Ochoa-Luna, C.,
Cartesian Trajectory Tracking of a 7-DOF Exoskeleton Robot Based on Human Inverse Kinematics,
SMCS(49), No. 3, March 2019, pp. 600-611.
IEEE DOI 1902
Robots, Exoskeletons, Kinematics, Elbow, Shoulder, Medical treatment, Wrist, Backstepping controller, exoskeleton robots, robotic rehabilitation 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

Ugurlu, B., Oshima, H., Sariyildiz, E., Narikiyo, T., Babic, J.,
Active Compliance Control Reduces Upper Body Effort in Exoskeleton-Supported Walking,
HMS(50), No. 2, April 2020, pp. 144-153.
IEEE DOI 2004
Compliance control, locomotion control, lower body exoskeleton 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

Hussain, S., Jamwal, P.K., van Vliet, P., Ghayesh, M.H.,
State-of-the-Art Robotic Devices for Wrist Rehabilitation: Design and Control Aspects,
HMS(50), No. 5, October 2020, pp. 361-372.
IEEE DOI 2009
Wrist, Rehabilitation robotics, Exoskeletons, Medical treatment, Brushless DC motors, Actuation, control paradigm, wrist orthosis BibRef

Jamwal, P.K., Hussain, S., Tsoi, Y.H., Xie, S.Q.,
Musculoskeletal Model for Path Generation and Modification of an Ankle Rehabilitation Robot,
HMS(50), No. 5, October 2020, pp. 373-383.
IEEE DOI 2009
Rehabilitation robotics, Ligaments, Joints, Bones, Springs, Ankle joint musculoskeletal modeling, robot path generation and modification 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

Liu, D.X.[Du-Xin], Xu, J.[Jing], Chen, C.J.[Chun-Jie], Long, X.G.[Xing-Guo], Tao, D.C.[Da-Cheng], Wu, X.Y.[Xin-Yu],
Vision-Assisted Autonomous Lower-Limb Exoskeleton Robot,
SMCS(51), No. 6, June 2021, pp. 3759-3770.
IEEE DOI 2106
Legged locomotion, Exoskeletons, Planning, Cameras, Visualization, Decision making, Autonomous decision-making, lower-limb exoskeleton robot 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

Wang, X.Y.[Xiang-Yang], Guo, S.[Sheng], Qu, B.J.[Bo-Jian], Bai, S.P.[Shao-Ping],
Design and Experimental Verification of a Hip Exoskeleton Based on Human-Machine Dynamics for Walking Assistance,
HMS(53), No. 1, February 2023, pp. 85-97.
IEEE DOI 2301
Exoskeleton, Wearable robots, Legged locomotion, Hip, Dynamics, hip exoskeleton, parallel mechanism, walking assistance, wearable robot BibRef

Verdel, D.[Dorian], Sahm, G.[Guillaume], Bastide, S.[Simon], Bruneau, O.[Olivier], Berret, B.[Bastien], Vignais, N.[Nicolas],
Influence of the Physical Interface on the Quality of Human-Exoskeleton Interaction,
HMS(53), No. 1, February 2023, pp. 44-53.
IEEE DOI 2301
Exoskeletons, Elbow, Robot sensing systems, Particle measurements, Atmospheric measurements, Force measurement, self-aligning mechanism BibRef

Wijegunawardana, I.[Isira], Ranaweera, R.K.P.S., Gopura, R.A.R.C.,
Lower Extremity Posture Assistive Wearable Devices: A Review,
HMS(53), No. 1, February 2023, pp. 98-112.
IEEE DOI 2301
Assistive devices, Wearable computers, Databases, Patents, Pain, Exoskeletons, Stress, Bodyweight support, work-related musculoskeletal disorders (WMSDs) 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

Li, G.X.[Guo-Xin], Li, Z.J.[Zhi-Jun], Su, C.Y.[Chun-Yi], Xu, T.[Tian],
Active Human-Following Control of an Exoskeleton Robot With Body Weight Support,
Cyber(53), No. 11, November 2023, pp. 7367-7379.
IEEE DOI 2310
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


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

Charoenseang, S.[Siam], Panjan, S.[Sarut],
4 DOF Exoskeleton Robotic Arm System for Rehabilitation and Training,
DHM18(147-157).
Springer DOI 1807
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,
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Hoermann, S., Collins, J., Regenbrecht, H.,
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3DUI15(163-164)
IEEE DOI 1511
augmented reality BibRef

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Kinematics Analysis Multimedia System for Rehabilitation,
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IMEV14(396-406).
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Matthew, R.P.[Robert Peter], Kurillo, G.[Gregorij], Han, J.J.[Jay J.], Bajcsy, R.[Ruzena],
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ACVR14(570-583).
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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)
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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).
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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,
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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,
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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).
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Track rehab efforts. BibRef

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


Last update:Mar 16, 2024 at 20:36:19