The DOI matches its Crossref record; 106 of the 107 references it cites were found in a registry or an index.
Biofeedback in rehabilitation
Open accessAbstract
This paper reviews the literature relating to the biofeedback used in physical rehabilitation. The biofeedback methods used in rehabilitation are based on biomechanical measurements and measurements of the physiological systems of the body. The physiological systems of the body which can be measured to provide biofeedback are the neuromuscular system, the respiratory system and the cardiovascular system. Neuromuscular biofeedback methods include electromyography (EMG) biofeedback and real-time ultrasound imaging (RTUS) biofeedback. EMG biofeedback is the most widely investigated method of biofeedback and appears to be effective in the treatment of many musculoskeletal conditions and in post cardiovascular accident (CVA) rehabilitation. RTUS biofeedback has been demonstrated effective in the treatment of low back pain (LBP) and pelvic floor muscle dysfunction. Cardiovascular biofeedback methods have been shown to be effective in the treatment of a number of health conditions such as hypertension, heart failure, asthma, fibromyalgia and even psychological disorders however a systematic review in this field has yet to be conducted. Similarly, the number of large scale studies examining the use of respiratory biofeedback in rehabilitation is limited. Measurements of movement, postural control and force output can be made using a number of different devices and used to deliver biomechanical biofeedback. Inertial based sensing biofeedback is the most widely researched biomechanical biofeedback method, with a number of studies showing it to be effective in improving measures of balance in a number of populations. Other types of biomechanical biofeedback include force plate systems, electrogoniometry, pressure biofeedback and camera based systems however the evidence for these is limited. Biofeedback is generally delivered using visual displays, acoustic or haptic signals, however more recently virtual reality (VR) or exergaming technology have been used as biofeedback signals. VR and exergaming technology have been primarily investigated in post-CVA rehabilitation, however, more recent work has shown this type of biofeedback to be effective in improving exercise technique in musculoskeletal populations. While a number of studies in this area have been conducted, further large scale studies and reviews investigating different biofeedback applications in different clinical populations are required.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Force plate systems provide feedback on balance, movement, and gait and have been shown to reduce the incidence of falls.24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“Moderate exercise, integrative neuromuscular training, Tai Chi, and Virtual Reality (VR) based exergaming show promise in improving postural stability and physical functioning.5,24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“Providing patients with EMDR,4 CBT,9,12,17 biofeedback24 or rTMS26,33 may enable them to gain control over physical processes, allowing for improved functional task performance and increased autonomy in their rehabilitation.24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
The cited source says what the claim attributes to it.
In the citing paper
“The addition of VR and therapeutic exergames offer patients opportunities to engage in meaningful, intensive, and enjoyable tasks related to their real-life interests and daily activities.24”
From A Review of Movement and Functional Impairments in Fibromyalgia: Implications for Targeted Treatment (2025) · cites this paper as [24]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Virtual Reality–Augmented Rehabilitation for Patients Following Stroke
Merians, A. S., Jack, D., Boian, R., Tremaine, M. M., Burdea, G., Adamovich, S., Recce, M. L., & Howard Poizner, A. (2002) · Physical Therapy · doi:10.1093/ptj/82.9.898 · Cited by 570
Karavidas, M. K., Lehrer, P. M., Vaschillo, E., Vaschillo, B., Marin, H., Buyske, S., Malinovsky, I., Radvanski, D., & Hassett, A. (2007) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-006-9029-z · Cited by 440
The Use of Ultrasound Imaging of the Abdominal Drawing-in Maneuver in Subjects With Low Back Pain
Teyhen, D. S., Miltenberger, C. E., Deiters, H. M., Toro, Y. M. D., Pulliam, J. N., Childs, J. D., Boyles, R. E., & Flynn, T. W. (2005) · Journal of Orthopaedic and Sports Physical Therapy · doi:10.2519/jospt.2005.35.6.346 · Cited by 415
Standing balance training: effect on balance and locomotion in hemiparetic adults.
Winstein, C., Gardner, E. R., McNeal, D. R., Barto, P. S., & De, N. (1989) · PubMed · Cited by 337
Zucker, T. L., Samuelson, K. W., Muench, F., Greenberg, M. A., & Gevirtz, R. N. (2009) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-009-9085-2 · Cited by 335
Recent developments in biofeedback for neuromotor rehabilitation
Huang, H., Wolf, S. L., & He, J. (2006) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-3-11 · Cited by 333
Geiger, R. A., Allen, J. B., O’Keefe, J., & Hicks, R. R. (2001) · Physical Therapy · doi:10.1093/ptj/81.4.995 · Cited by 333
Yamanouchi, K., Shinozaki, T., Chikada, K., Nishikawa, T., Ito, K., Shimizu, S., Ozawa, N., Suzuki, Y., Maeno, H., Kato, K., et al. (1995) · Diabetes Care · doi:10.2337/diacare.18.6.775 · Cited by 330 · cited 1×
“Much work has been conducted evaluating pedometers as a means of improving exercise compliance in people with diabetes, obesity and congestive heart failure [72-74].”
BackgroundHassett, A. L., Radvanski, D. C., Vaschillo, E. G., Vaschillo, B., Sigal, L. H., Karavidas, M. K., Buyske, S. G., & Lehrer, P. M. (2007) · Applied Psychophysiology and Biofeedback · doi:10.1007/s10484-006-9028-0 · Cited by 282
Balance Retraining After Stroke Using Force Platform Biofeedback
Nichols, D. S. (1997) · Physical Therapy · doi:10.1093/ptj/77.5.553 · Cited by 270
Research works printed but not linked: 1
- 10.1007/s10484-010-9140-z · DOI
Cited by
Sorted by citations
Items 201–300 of 761
Yasuda, K., Kaibuki, N., Harashima, H., & Iwata, H. (2017) · Somatosensory & Motor Research · doi:10.1080/08990220.2017.1292236 · Cited by 16
Hruby, L. A., Sturma, A., & Aszmann, O. C. (2019) · Journal of Visualized Experiments · doi:10.3791/59839 · Cited by 16
Campo, M. A., Zadro, J. R., Pappas, E., Monticone, M., Secci, C., Scalzitti, D. A., Findley, J. L., & Graham, P. L. (2021) · Musculoskeletal Science and Practice · doi:10.1016/j.msksp.2021.102317 · Cited by 16
Khajuria, A., & Joshi, D. (2022) · Medical Engineering & Physics · doi:10.1016/j.medengphy.2022.103772 · Cited by 16
Mennella, C., Maniscalco, U., Pietro, G. D., & Esposito, M. (2023) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2023.107665 · Cited by 16
Intsy: a low-cost, open-source, wireless multi-channel bioamplifier system
Erickson, J. C., Hayes, J. A., Bustamante, M. J., Joshi, R., Rwagaju, A., Paskaranandavadivel, N., & Angeli, T. R. (2018) · Physiological Measurement · doi:10.1088/1361-6579/aaad51 · Cited by 16
Lírio-Romero, C., Torres-Lacomba, M., Gómez-Blanco, A., Acero-Cortés, A., Retana-Garrido, A., de la Villa, P., & Sánchez-Sánchez, B. (2020) · Physiotherapy · doi:10.1016/j.physio.2020.02.002 · Cited by 15
Kaźmierczak, K., Wareńczak, A., Miedzyblocki, M., & Lisiński, P. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph192416925 · Cited by 15
Matsi, A. E., Billis, E. V., Lampropoulou, S., Xergia, S. A., Τσεκούρα, Μ., & Fousekis, K. (2023) · Applied Sciences · doi:10.3390/app132312743 · Cited by 15
Park, C., & Lee, B.-C. (2024) · Bioengineering · doi:10.3390/bioengineering11050460 · Cited by 15
Sturma, A., Goebel, P. M., Herceg, M., Ge, N., Roche, A. D., Fialka‐Moser, V., & Aszmann, O. C. (2014) · Biosystems & biorobotics · doi:10.1007/978-3-319-08072-7_33 · Cited by 15
Interpersonal synergies: static prehension tasks performed by two actors
Solnik, S., Reschechtko, S., Wu, Y.-H., Zatsiorsky, V. M., & Latash, M. L. (2016) · Experimental Brain Research · doi:10.1007/s00221-016-4632-6 · Cited by 15
Baniqued, P. D. E., Baldovino, R. G., & Bugtai, N. T. (2015) · International Conference on Humanoid, Nanotechnology, Information Technology,Communication and Control, Environment and Management · doi:10.1109/hnicem.2015.7393198 · Cited by 15
Overground gait training using virtual reality aimed at gait symmetry
Shideler, B. L., Martelli, D., Prado, A., & Agrawal, S. K. (2021) · Human Movement Science · doi:10.1016/j.humov.2021.102770 · Cited by 15
Idrobo-Ávila, E., Correa, H. L., Muñoz-Bolaños, F., van Noorden, L., & Vargas-Cañas, R. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.103095 · Cited by 15
Kirchner, E. A., & Bütefür, J. (2022) · Current Robotics Reports · doi:10.1007/s43154-022-00076-7 · Cited by 15
Guo, L., Gong, X., Li, Y., Zhang, D., Elsadek, M., Yun, J., Hassan, A., Yao, M., & Li, N. (2025) · Land · doi:10.3390/land14020317 · Cited by 15
Sensor System for Precision Shooting Evaluation and Real-time Biofeedback
Kos, A., Umek, A., Marković, S., & Dopsaj, M. (2019) · Procedia Computer Science · doi:10.1016/j.procs.2019.01.228 · Cited by 14
Drigas, A. S., Mitsea, E., & Skianis, C. (2022) · Technium BioChemMed · doi:10.47577/biochemmed.v3i2.6628 · Cited by 14
Visual Recovery after Primary Retinal Detachment Surgery: Biofeedback Rehabilitative Strategy
Vingolo, E. M., Fragiotta, S., Domanico, D., Limoli, P. G., Nebbioso, M., & Spadea, L. (2016) · Journal of Ophthalmology · doi:10.1155/2016/8092396 · Cited by 14
EMG map image processing for recognition of fingers movement
Topalović, I., Graovac, S., & Popović, D. B. (2019) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2019.102364 · Cited by 14
A Metaphor-Based Technical Framework for Musical Sonification in Movement Rehabilitation
Kantan, P. R., Spaich, E. G., & Dahl, S. (2021) · International Conference on Auditory Display (ICAD) · doi:10.21785/icad2021.008 · Cited by 14
González-González, A. M., Pellitero, M. T., Tejerina, N. L., Soto-Goñi, X., Cuenca‐Zaldívar, J. N., & Romero, E. A. S. (2025) · BMC Oral Health · doi:10.1186/s12903-025-06789-3 · Cited by 13
Electromyography-biofeedback for chronic low back pain: A qualitative cohort study
Sadora, J., Vilsmark, E. S., Bashara, A., Burton, D., Paschali, M., Pester, B., Curiel, M., Edwards, R. R., & Lazaridou, A. (2023) · Complementary Therapies in Medicine · doi:10.1016/j.ctim.2023.102922 · Cited by 13
Assessment, patient selection, and rehabilitation of nerve transfers
Bateman, E. A., Larocerie‐Salgado, J., Ross, D. C., Miller, T. A., & Pripotnev, S. (2023) · Frontiers in Rehabilitation Sciences · doi:10.3389/fresc.2023.1267433 · Cited by 13
Khaleghi, A., Narimani, A., Aghaei, Z., Banaraki, A. K., & Hassani‐Abharian, P. (2024) · JMIR Serious Games · doi:10.2196/34535 · Cited by 13
Kurt, M., Savaş, D., Şimşek, T. T., & Yiş, U. (2024) · Muscle & Nerve · doi:10.1002/mus.28084 · Cited by 13
Jogna, F., Graenicher, A., Rey-Millet, Q., Groz, A., Grasset, J. D., Stollar, F., Coen, M., & Faivre, A. (2025) · Pain Management · doi:10.1080/17581869.2025.2502311 · Cited by 13
The validity and usability of an eight marker model for avatar-based biofeedback gait training
Booth, A., van der Krogt, M. M., Buizer, A. I., Steenbrink, F., & Harlaar, J. (2019) · Clinical Biomechanics · doi:10.1016/j.clinbiomech.2019.08.013 · Cited by 13
Research Advances in ADHD and Technology
Cibrian, F. L., Hayes, G. R., & Lakes, K. D. (2021) · Synthesis lectures on technology and health · doi:10.1007/978-3-031-01606-6 · Cited by 13
Rehabilitation According to the Biological Feedback
Kurgaev, O., & Palagin, A. V. (2021) · IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS) · doi:10.1109/idaacs53288.2021.9660953 · Cited by 13
Lee, C., Ahn, J., & Lee, B.-C. (2023) · Bioengineering · doi:10.3390/bioengineering10101142 · Cited by 13
Merchán-Baeza, J. A., González‐Sánchez, M., & Vargas, A. I. C. (2015) · BioMedical Engineering OnLine · doi:10.1186/s12938-015-0047-z · Cited by 13
Vieira, D. P., Silva, M. B., Melo, M. C., & Soares, A. B. (2016) · Disability and Rehabilitation · doi:10.3109/09638288.2016.1146359 · Cited by 13
Biosensors and Biofeedback in Clinical Psychology
Mancuso, V., Stramba-Badiale, C., Cavedoni, S., & Cipresso, P. (2020) · Elsevier eBooks · doi:10.1016/b978-0-12-818697-8.00002-9 · Cited by 13
Caetano, I., Alves, J., Gonçalves, J., Martins, M., & Santos, C. P. (2016) · IEEE International Conference on Autonomous Robot Systems and Competitions · doi:10.1109/icarsc.2016.34 · Cited by 13
Riek, L. M., Pfohl, K., & Zajac, J. A. (2022) · Journal of Electromyography and Kinesiology · doi:10.1016/j.jelekin.2022.102647 · Cited by 12
Stawiarska, E. M., & Stawiarski, M. (2023) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph20043754 · Cited by 12
Chen, K., Han, J., Baldauf, H., Wang, Z., Chen, D. D., Kato, A., Ward, J. A., & Kunze, K. S. (2023) · Augmented Humans International Conference (AHs) · doi:10.1145/3582700.3582727 · Cited by 12
Petreca, B. B., Tajadura‐Jiménez, A., Vidal, L. T., O’Nascimento, R., Seifi, H., Ley-Flores, J., Singh, A., Bianchi‐Berthouze, N., Obrist, M., & Baurley, S. L. (2023) · CHI Conference Extended Abstracts on Human Factors in Computing Systems (CHI EA) · doi:10.1145/3544549.3573807 · Cited by 12
Cinnera, A. M., Verna, V., Marucci, M., Tavernese, A., Magnotti, L., Matano, A., D’Acunto, C., Paolucci, S., Morone, G., Betti, V., et al. (2024) · Brain Sciences · doi:10.3390/brainsci14030283 · Cited by 12
Sancak, E. B., Akbaş, A., Kurt, Ö., Alan, C., & Ersay, A. R. (2016) · Urology Research and Practice · doi:10.5152/tud.2016.39114 · Cited by 12
Skin Mountable Capillaric Strain Sensor with Ultrahigh Sensitivity and Direction Specificity
Yepes, L. R., Demir, E., Lee, J. Y., Sun, R., Smuck, M. W., & Araci, I. E. (2020) · Advanced Materials Technologies · doi:10.1002/admt.202000631 · Cited by 12
fNIRS-based adaptive visuomotor task improves sensorimotor cortical activation
Zheng, Y., Tian, B., Zhuang, Z., Zhang, Y., & Wang, D. (2022) · Journal of Neural Engineering · doi:10.1088/1741-2552/ac823f · Cited by 12
Tiryaki, P., Çelik, D., Bilsel, K., & Erşen, A. (2022) · American Journal of Physical Medicine & Rehabilitation · doi:10.1097/phm.0000000000002111 · Cited by 12
The Use of Biofeedback on Students: a Systematic Review
Rodrigues, R. N. G., Tucci, A. M., & Viana, M. D. B. (2021) · Trends in Psychology · doi:10.1007/s43076-021-00109-8 · Cited by 11
Unique Features of the US Department of Defense Multidisciplinary Concussion Clinics
Lee, K. M., Greenhalgh, W. M., Sargent, P., Chae, H., Klimp, S., Engel, S., Merritt, B. P., Kretzmer, T. S., Bajor, L., Scott, S., et al. (2019) · Journal of Head Trauma Rehabilitation · doi:10.1097/htr.0000000000000526 · Cited by 11
Noninvasive augmented sensory feedback in poststroke hand rehabilitation approaches
Cappello, L., Baldi, R., Engels, L. F., & Cipriani, C. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-822828-9.00006-x · Cited by 11
Bonini‐Rocha, A. C., de Andrade, A. L. S., Pereira, R. D. S., de Moraes, A. M., Matheus, L. B. G., Fonseca, S. T., Ribeiro, A. L. D. A., & Martins, W. R. (2022) · Journal of Hand Therapy · doi:10.1016/j.jht.2022.05.001 · Cited by 11
Hacad, C. R., Lucon, M., Milhomem, S. A. R., Bruschini, H., & Tanaka, C. (2022) · International braz j urol · doi:10.1590/s1677-5538.ibju.2022.0056 · Cited by 11
Parel, I., Candoli, V., Filippi, M. V., Padolino, A., Merolla, G., Sanniti, S., Galassi, R., Paladini, P., & Cutti, A. G. (2022) · JMIR Research Protocols · doi:10.2196/35757 · Cited by 11
Escamilla-Nunez, R., Gouda, A., & Andrysek, J. (2023) · IEEE Transactions on Neural Systems and Rehabilitation Engineering · doi:10.1109/tnsre.2023.3282216 · Cited by 11
Cinnera, A. M., Bonnı̀, S., D’Acunto, A., Maiella, M., Ferraresi, M., Casula, E. P., Pezzopane, V., Tramontano, M., Iosa, M., Paolucci, S., et al. (2023) · Trials · doi:10.1186/s13063-023-07849-1 · Cited by 11
Zasada, M., Gorkovenko, A. V., Strafun, S. S., Vasylenko, D. A., Pilewska, W., Kulyk, Y. A., & Kostyukov, A. I. (2020) · Neurophysiology · doi:10.1007/s11062-021-09896-3 · Cited by 11
Yuan, Y., Xu, M., Yang, H., Sun, B., Li, Y., Zhang, N., Wang, G., & Su, F. (2021) · Frontiers in Pediatrics · doi:10.3389/fped.2021.638120 · Cited by 11
Fukuhara, S., & Oka, H. (2019) · Advanced Biomedical Engineering · doi:10.14326/abe.8.185 · Cited by 10
Cinnera, A. M., Ciancarelli, I., Paolucci, T., Merla, A., Nicola, M. D., Perpetuini, D., D’Arienzo, M., Genovesi, G., Moretti, A., Russo, E. F., et al. (2024) · Neurorehabilitation · doi:10.1177/10538135241296010 · Cited by 10
ESTRATÉGIAS DE INTERVENÇÃO PARA MELHORAR A DEGLUTIÇÃO EM INDIVÍDUOS COM PARKINSON
PASTANA, I. C., SOUZA, M. E. G. M. C. D., & de Leão, R. E. B. (2025) · Revista Contemporânea · doi:10.56083/rcv5n9-048 · Cited by 10
Lemoyne, R. C., & Mastroianni, T. (2018) · Journal of Mechanics in Medicine and Biology · doi:10.1142/s0219519418500057 · Cited by 10
Jochum, F., Garbin, O., Godet, J., Ragueneau, M., Meyer, C., Billecocq, S., Lecointre, L., Akladios, C. Y., & Host, A. (2021) · Journal of Gynecology Obstetrics and Human Reproduction · doi:10.1016/j.jogoh.2021.102280 · Cited by 10
Kokić, I. Š., Vuksanic, M., Kokić, T., Perić, I., & Duvnjak, I. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11113182 · Cited by 10
Ruchiwit, M., Vuthiarpa, S., Ruchiwit, K., Muijeen, K., & Phanphairoj, K. (2024) · Clinical Practice and Epidemiology in Mental Health · doi:10.2174/0117450179276691231229071003 · Cited by 12
Li, S., Pham, H. T., Karunarathne, M. S., Lee, Y. S., Ekanayake, S. W., & Pathirana, P. N. (2015) · Mathematical Problems in Engineering · doi:10.1155/2015/617840 · Cited by 10
EMG based biofeedback system using a virtual reality method
Jayarathne, M. M. R. K., Wickramanayake, D. K. W. W. M. S., Afsheenjinan, A., Ranaweera, R. D., & Weerasingha, V. (2015) · IEEE International Conference on Industrial and Information Systems (ICIIS) · doi:10.1109/iciinfs.2015.7398995 · Cited by 10
Tafreshi, A. S., Riener, R., & Klamroth-Marganska, V. (2016) · Frontiers in Physiology · doi:10.3389/fphys.2016.00612 · Cited by 10
Pizzi, S. D., Bellomo, R. G., Carmignano, S. M., Ancona, E., Franciotti, R., Supplizi, M., Barassi, G., ONOFRJ, M. C., Bonanni, L., & Saggini, R. (2017) · Medicine · doi:10.1097/md.0000000000008732 · Cited by 11
Evaluation of Optimal Vibrotactile Feedback for Force-Controlled Upper Limb Myoelectric Prostheses
Gonzalez-Rodriguez, A., Ramón, J., Morell, V., Garcia, G. J., Pomares, J., Jara, C. A., & Úbeda, A. (2019) · Sensors · doi:10.3390/s19235209 · Cited by 10
Feasibility of the Archercise biofeedback device to strengthen foot musculature
Latey, P. J., Eisenhuth, J., McKay, M. J., Hiller, C. E., Sureshkumar, P., Nightingale, E. J., & Burns, J. (2020) · Journal of Foot and Ankle Research · doi:10.1186/s13047-020-00394-z · Cited by 10
Automatic Emotional Balancing in Game Design: Use of Emotional Response to Increase Player Immersion
Dworak, W. S., Filgueiras, E., & Valente, J. P. S. D. S. (2020) · Lecture notes in computer science · doi:10.1007/978-3-030-49760-6_30 · Cited by 10
Supinski, G. S., Valentine, E. N., Netzel, P. F., Schroder, E. A., Wang, L., & Callahan, L. A. (2020) · Critical Care Medicine · doi:10.1097/ccm.0000000000004544 · Cited by 10
A Wearable Vibrotactile Biofeedback System Targeting Gait Symmetry of Lower-limb Prosthetic Users
Escamilla-Nunez, R., Michelini, A., & Andrysek, J. (2020) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc44109.2020.9176666 · Cited by 10
la Fuente, C. D., Silvestre, R., Baechler, P., Gemigniani, A., Grunewaldt, K., Vassiliu, M., Wodehouse, V., Delgado, M., & Carpes, F. P. (2020) · Journal of Manipulative and Physiological Therapeutics · doi:10.1016/j.jmpt.2019.10.017 · Cited by 10
Tafreshi, A. S., Riener, R., & Klamroth-Marganska, V. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00327 · Cited by 10
Favre, J., Cantaloube, A., & Jolles, B. M. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12165310 · Cited by 10
Ng, H. H., Wu, C. W., Hsu, H., Huang, C., Hsu, A., Chao, Y., Jung, T., & Chuang, C. (2024) · JMIR Formative Research · doi:10.2196/55478 · Cited by 9
Jokar, F., Fani, M., Esfahani, N. T., & Sabahi, R. (2024) · International Urogynecology Journal · doi:10.1007/s00192-024-06011-y · Cited by 9
Li, G., Doman, C., & Suresh, N. L. (2019) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2019.8856982 · Cited by 9
Rimini, D., Salvalaggio, S., Pregnolato, G., Alhelou, M., Berlingieri, C., Mascotto, E., Turolla, A., Ariano, P., Celadon, N., & Ahmed, D. (2020) · IEEE International Symposium on Medical Measurements and Applications (MeMeA) · doi:10.1109/memea49120.2020.9137140 · Cited by 9
Kokić, T., Pavić, R., Vuksanic, M., Jelica, S., Šumanovac, A., Banić, T., Ostović, H., & Kokić, I. Š. (2023) · Journal of Personalized Medicine · doi:10.3390/jpm13121716 · Cited by 9
Kuo, L., Yang, C.-J., Lin, C., Jou, I., Yang, Y., Yeh, C.-H., Lin, C., & Hsu, H. (2019) · European Journal of Physical and Rehabilitation Medicine · doi:10.23736/s1973-9087.19.05667-3 · Cited by 9
Sanford, S., Liu, M., & Nataraj, R. (2021) · Journal of Sport Rehabilitation · doi:10.1123/jsr.2020-0234 · Cited by 9
Zhou, X.-D., Wei, H.-G., & Ai, F. (2022) · World Journal of Gastrointestinal Oncology · doi:10.4251/wjgo.v14.i6.1187 · Cited by 9
Touchless touch with biosignal transfer for online communication
Hemmerling, D., Stroinski, M., Kwarciak, K., Trusiak, K., Szymkowski, M., Celniak, W., Frier, W., Georgiou, O., & Maksymenko, M. (2022) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/3536221.3556585 · Cited by 9
Investigation of the Effectiveness of TecnoBody Devices in Rehabilitation
Üzümcü, B., Açar, G., Konakoğlu, G., & Mutuş, R. (2024) · İstanbul Gelişim Üniversitesi Sağlık Bilimleri Dergisi · doi:10.38079/igusabder.1418692 · Cited by 9
Complementary and Alternative Medicine
Devine, M., & Hayes, M. (2016) · Springer eBooks · doi:10.1007/978-3-319-04414-9_47 · Cited by 9
Towards a systematic approach to real-time sonification design for surface electromyography
Peres, S. C., Verona, D., Nisar, T., & Ritchey, P. (2016) · Displays · doi:10.1016/j.displa.2016.05.006 · Cited by 9
Russo, G. A., Oliveri, S., Cincidda, C., Guiddi, P., & Pravettoni, G. (2020) · Journal of Public Health Research · doi:10.4081/jphr.2020.1782 · Cited by 9
Kos, A., & Umek, A. (2018) · Human-computer interaction series · doi:10.1007/978-3-319-91349-0_2 · Cited by 9
Impact of Visual Biofeedback of Trunk Sway Smoothness on Motor Learning during Unipedal Stance
Cruz‐Montecinos, C., Vargas, A. I. C., Muñoz, C., Flores, D., Ellsworth, J., la Fuente, C. D., Calatayud, J., Rivera‐Lillo, G., Soto, V., Tapia, C., et al. (2020) · Sensors · doi:10.3390/s20092585 · Cited by 9
Cieślik, B., Wrzeciono, A., Mazurek, J., Federico, S., Szczepańska-Gieracha, J., & Kiper, P. (2024) · Games for Health Journal · doi:10.1089/g4h.2023.0109 · Cited by 8
Cinnera, A. M., Ciancarelli, I., Marrano, S., Palagiano, M., Federici, E., Bisirri, A., Iosa, M., Paolucci, S., Koch, G., & Morone, G. (2024) · Brain Sciences · doi:10.3390/brainsci14090917 · Cited by 8
Wearable Sensors and Artificial Intelligence for the Diagnosis of Parkinson’s Disease
Benyoucef, Y., Melliti, I., Harmouch, J., Asadi, B., Mastro, A. D., Lapuente‐Hernández, D., & Herrero, P. (2025) · Journal of Clinical Medicine · doi:10.3390/jcm14124207 · Cited by 8
Wähnert, S., & Müller-Plath, G. (2021) · Psych · doi:10.3390/psych3040054 · Cited by 8
Highly-Individualized Physical Therapy Instruction Beyond the Clinic Using Wearable Inertial Sensors
Rawashdeh, S. A., Reimann, E., & Uhl, T. L. (2022) · IEEE Access · doi:10.1109/access.2022.3143765 · Cited by 8
Bertucco, M., Nardon, M., Mueske, N. M., Sandhu, S., Rethlefsen, S. A., Wren, T. A. L., & Sanger, T. D. (2022) · Physical & Occupational Therapy In Pediatrics · doi:10.1080/01942638.2022.2151391 · Cited by 8
Yang, X., Zhong, S., Yang, S., He, M., Xu, X., He, S., Fan, G., & Liu, L. (2023) · JMIR Serious Games · doi:10.2196/48354 · Cited by 8
How Biofeedback With Surface EMG Can Contribute to the Diagnosis and Treatment of AMI in the Knee
Richaud, T., Lacaze, K., Fassio, A., Nicolas, P., Ourliac, M., Hennart, B., Ina, J. G., Sonnery‐Cottet, B., & Cavaignac, É. (2024) · Video Journal of Sports Medicine · doi:10.1177/26350254241241084 · Cited by 8
Aydos, İ. A., Semerci, R., Savaş, E. H., Gulersoy, A., & Ürey, H. (2024) · Journal of Pediatric Nursing · doi:10.1016/j.pedn.2024.09.008 · Cited by 9
Thomson, C. J., Mino, F. R., Lopez, D. R., Maitre, P. P., Edgley, S. R., & George, J. A. (2024) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/s12984-024-01529-0 · Cited by 8
Validation of Low-Cost IMUs for Telerehabilitation Exercises
Caramia, F., D’Angelantonio, E., Lucangeli, L., & Camomilla, V. (2025) · Sensors · doi:10.3390/s25103129 · Cited by 8
Metadata
- Authors
- Giggins, O. M., Persson, U., & Caulfield, B.
- Affiliations
- University College Dublin (IE)
- Corresponding author
- Giggins, Oonagh M
- Venue
- Journal of NeuroEngineering and Rehabilitation
- Published
- 2013
- Volume
- 10
- Issue
- 1
- Pages
- 60
- ISSN
- 1743-0003 (ISSN-L)
- PMC
- PMC3687555
- OpenAlex
- W2158721732
- Cited by
- 760
- References
- 107
- Citations by year
- 2026: 75 · 2025: 86 · 2024: 90 · 2023: 72 · 2022: 59 · 2021: 61 · 2020: 87 · 2019: 55 · 2018: 52 · 2017: 27 · 2016: 49 · 2015: 32 · 2014: 15
- FWCI
- 5.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Journal of NeuroEngineering and Rehabilitation (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Lenus, The Irish Health Repository (Dr Steevens Hospital Library) (submittedVersion)
- Funders
- Science Foundation Ireland
- Topics
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Health Sciences › Health Professions › Physical Therapy, Sports Therapy and Rehabilitation › Medical Practices and Rehabilitation
- Physical Sciences › Engineering › Biomedical Engineering › Muscle activation and electromyography studies
- Keywords
- biofeedback, physical rehabilitation, EMG biofeedback, real-time ultrasound, respiratory biofeedback, inertial sensing, balance, stroke rehabilitation, low back pain, pelvic floor dysfunction, virtual reality, exergames, musculoskeletal disorders, haptic feedback
- MeSH terms
- Biofeedback, Psychology, Humans, Rehabilitation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
