The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
MotionTalk: personalized home rehabilitation system for assisting patients with impaired mobility
Open accessAbstract
Physical injury, stroke, trauma, traumatic brain injury and spinal cord injury rank among the top causes of disability. There are a total of 54 million people in the US requiring rehabilitative assistance of which 15.3 million people are in the age groups of 18-44. However, the compliance rate for patients performing rehabilitation exercises in the home environment is poor. In this paper, we design and prototype a personalized home rehabilitation system, MotionTalk, for the real time quantitative assessment of mobility. Performance of rehabilitation is designed to be assessed using the changes in mobility, reflected in the exercises performed by patients at home with respect to the same exercises performed in the clinic. Our system is capable of capturing motion using Microsoft Kinect and analyzing the position and rotation information to give scores for assessing rehabilitation progress. In comparison to conventional rehabilitation systems, MotionTalk is an inexpensive (<$150 compared to conventional systems costing >$1000), less intrusive and personalized home rehabilitation system, which was developed and tested using data from able-bodied volunteers at Georgia Institute of Technology.
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The design requirements align with several other research studies that have extracted design requirements for recovery, such as post-operative cancer care, physical injury, cognitive rehabilitation, and recovery in critical care units.
“Our design requirements align with several other research studies that have extracted design requirements for recovery, such as post-operative cancer care [4], physical injury [73, 82], cognitive rehabilitation [36], and recovery in critical care units[66].”
From A Data Visualization Tool for Patients and Healthcare Providers to Communicate during Inpatient Stroke Rehabilitation (2024) · cites this paper as [73]
The Introduction identifies physical injury among conditions requiring rehabilitation, and §2.1 (Use Cases; page unavailable) describes the functions designed for MotionTalk’s home-rehabilitation system. This supports citing MotionTalk as a physical-injury rehabilitation design study, but our copy does not report extracting design requirements for recovery. (LLM, conf=0.79)
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Peng, H., Long, F., & Ding, C. (2005) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2005.159 · Cited by 10,790
Quaternions and matrices of quaternions
Zhang, F. (1997) · Linear Algebra and its Applications · doi:10.1016/0024-3795(95)00543-9 · Cited by 1,115
Physical Activity and Exercise Recommendations for Stroke Survivors
Gordon, N. F., Gulanick, M., Costa, F., Fletcher, G. F., Franklin, B. A., Roth, E. J., & Shephard, T. (2004) · Circulation · doi:10.1161/01.cir.0000126280.65777.a4 · Cited by 511
Full body gait analysis with Kinect
Gabel, M., Gilad-Bachrach, R., Renshaw, E., & Schuster, A. (2012) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2012.6346340 · Cited by 334
Spherical averages and applications to spherical splines and interpolation
Buss, S. R., & Fillmore, J. P. (2001) · ACM Transactions on Graphics · doi:10.1145/502122.502124 · Cited by 302
CERN Press Office. Geneva (2005) · Seminars in Anesthesia Perioperative Medicine and Pain · doi:10.1053/s0277-0326(05)00052-8 · Cited by 294
Physical Activity, Disability, and Quality of Life in Older Adults
Motl, R. W., & McAuley, E. (2010) · Physical Medicine and Rehabilitation Clinics of North America · doi:10.1016/j.pmr.2009.12.006 · Cited by 268
Towards Pervasive Physical Rehabilitation Using Microsoft Kinect
Chang, C., Lange, B. S., Zhang, M., Koenig, S. T., Requejo, P., Somboon, N., Sawchuk, A. A., & Rizzo, A. (2012) · International Conference on Pervasive Computing Technologies for Healthcare · doi:10.4108/icst.pervasivehealth.2012.248714 · Cited by 263
A feasibility study of an upper limb rehabilitation system using kinect and computer games
Pastor, I., Hayes, H., & Bamberg, S. J. M. (2012) · doi:10.1109/embc.2012.6346173 · Cited by 124
Influence of Physical Exercise on Traumatic Brain Injury Deficits: Scaffolding Effect
Archer, T. (2011) · Neurotoxicity Research · doi:10.1007/s12640-011-9297-0 · Cited by 95
Bland, D. C., Zampieri, C., & Damiano, D. L. (2011) · Brain Injury · doi:10.3109/02699052.2011.576306 · Cited by 90
The Use of a Game to Promote Arm Reach in Persons With Traumatic Brain Injury
Sietsema, J. M., Nelson, D. L., Mulder, R. M., Mervau-Scheidel, D., & White, B. E. (1993) · American Journal of Occupational Therapy · doi:10.5014/ajot.47.1.19 · Cited by 89
Bilateral upper-limb rehabilitation after stroke using a movement-based game controller
Hijmans, J. M., Hale, L. A., Satherley, J. A., McMillan, N. J., & King, M. (2011) · The Journal of Rehabilitation Research and Development · doi:10.1682/jrrd.2010.06.0109 · Cited by 70
Cancelliere, C., Cassidy, J. D., Côté, P., Hincapié, C. A., Hartvigsen, J., Carroll, L., Marras, C., Boyle, E., Kristman, V. L., Hung, R., et al. (2012) · Systematic Reviews · doi:10.1186/2046-4053-1-17 · Cited by 59
Development of a 3D immersive videogame to improve arm-postural coordination in patients with TBI
Ustinova, K. I., Leonard, W. A., Cassavaugh, N. D., & Ingersoll, C. D. (2011) · Journal of NeuroEngineering and Rehabilitation · doi:10.1186/1743-0003-8-61 · Cited by 52
Schwandt, M., Harris, J. E., Thomas, S. G., Keightley, M., Snaiderman, A., & Colantonio, A. (2011) · Journal of Head Trauma Rehabilitation · doi:10.1097/htr.0b013e31820e6858 · Cited by 48
Mumford, N., Duckworth, J., Thomas, P. R., Shum, D., Williams, G. P., & Wilson, P. H. (2010) · Brain Injury · doi:10.3109/02699051003652807 · Cited by 41
Cantin, J.-F., McFadyen, B. J., Doyon, J., SWAINE, B. R., Dumas, D., & Vallée, M. (2007) · Brain Injury · doi:10.1080/02699050701209972 · Cited by 41
A Wearable Rehabilitation Robotic Hand Driven by PM-TS Actuators
Wu, J., Huang, J., Wang, Y., & Xing, K. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-16587-0_41 · Cited by 40
Quaternion Dynamic Time Warping
Jabłoński, B. (2011) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2011.2177832 · Cited by 36
Slifer, K. J. (1997) · Brain Injury · doi:10.1080/026990597122954 · Cited by 36
Kinect-based rehabilitation system for patients with traumatic brain injury
Venugopalan, J., Cheng, C., Stokes, T. H., & Wang, M. D. (2013) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/embc.2013.6610578 · Cited by 35
Self-citationRhythmic exercises in rehabilitation of TBI patients: A case report
Goldshtrom, Y., Knorr, G., & Goldshtrom, I. (2009) · Journal of Bodywork and Movement Therapies · doi:10.1016/j.jbmt.2009.06.002 · Cited by 19
Dynamic Time Warping In Gait Classificationof Motion Capture Data
Świtoński, A., Michalczuk, A., Josiński, H., Polański, A., & KonradWojciechowski (2012) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.1083928 · Cited by 10
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Present and Future Trends in Consumer Health Informatics and Patient-Generated Health Data
Lai, A. M., Hsueh, P.-Y. S., Choi, Y. K., & Austin, R. R. (2017) · Yearbook of Medical Informatics · doi:10.15265/iy-2017-016 · Cited by 84
Person-Generated Health Data in Simulated Rehabilitation Using Kinect for Stroke: Literature Review
Dimaguila, G. L., Gray, K. M., & Merolli, M. (2018) · JMIR Rehabilitation and Assistive Technologies · doi:10.2196/rehab.9123 · Cited by 15
Ramesh, S. H., Ouskine, A., Khorasani, E., Ebrahimipour, M., Finestone, H., Chan, A. D. C., & Rajabiyazdi, F. (2024) · Graphics Interface · doi:10.1145/3670947.3670978 · Cited by 7
Hand Mobility Recovery Through Game Controlled by Gestures
Saman, O., & Stanciu, L. (2019) · IEEE International Symposium on Applied Computational Intelligence and Informatics (SACI) · doi:10.1109/saci46893.2019.9111632 · Cited by 5
Metadata
- Authors
- Venugopalan, J., Cheng, C.-W., & Wang, M. D.
- Affiliations
- Emory University (US)
- Georgia Institute of Technology (US)
- Venue
- Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics
- Publisher
- ACM
- Published
- 2014-09-20
- Volume
- 2014
- Pages
- 455-463
- PMC
- PMC5242025
- OpenAlex
- W2017681660
- Cited by
- 4
- References
- 24
- Citations by year
- 2024: 1 · 2019: 1 · 2018: 1 · 2017: 1
- FWCI
- 0.56
- Type
- conference paper
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Cancer Institute (U54CA119338)
- Topics
- Health Sciences › Medicine › Rehabilitation › Stroke Rehabilitation and Recovery
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Context-Aware Activity Recognition Systems
- Physical Sciences › Engineering › Biomedical Engineering › Prosthetics and Rehabilitation Robotics
- Keywords
- home-based rehabilitation, motion capture, Kinect sensor, mobility assessment, rehabilitation progress monitoring, low-cost rehabilitation device, stroke rehabilitation, traumatic brain injury, spinal cord injury, rehabilitation compliance, personalized rehabilitation
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