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One of the major contributor for the lower quality of living in the aged population, is the reduction in hand function. To mitigate this, several virtual-reality based hand rehabilitation/training systems have been developed.
However, most of these systems are solely controlled by hand gestures, and do not incorporate the force between the fingertips. Which is not the case for grabbing things in real life. With that in mind, the researchers assumed that a virtual-reality based hand rehabilitation/training system that incorporates force control into its input can be more beneficial in terms of recovering one's hand function.
To test out this claim, subjects were recruited and tasked to play a game using both input systems (wfc and wofc), while their brain activity while using both input system was simultaneously recorded using functional near infrared spectroscopy and compared
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| with force control (wfc) | Active Comparator | Users play the game using the conventional virtual reality input system with force control |
|
| without force control (wofc) | Experimental | Users play the game using the conventional virtual reality input system |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Virtual reality headset | Device | Meta-Quest 2 virtual reality headset was used in this study |
|
| Measure | Description | Time Frame |
|---|---|---|
| Oxygenated hemoglobin (HbO) | The Oxygenated hemoglobin (HbO) was measured while the participants play the game under both conditions | 1 hour |
| Game performance1 (Amount of grasp initiated) | This unitless metric counts the number of times the subject initiates a grasp while playing the game, a higher amount of grasp initiated signifies worst performance | 1 hour |
| Game performance2 (Memory task accuracy) | This percentage is calculated by dividing the amount of correct response by the total amount of response. A larger perrcentage represents better performance | 1 hour |
| Measure | Description | Time Frame |
|---|---|---|
| Manual dexterity | The manual dexterity of each participant was measured using the Purdue Pegboard Test at the beginning of the experiment | 5 minutes |
| Maximum voluntary pinch force | The maximum voluntary pinch force of each particapant were measured using the Jamar pinch dynamometer at the beginning of the experiment |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Fong-Chin Su, PhD | Chair Professor | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| National Cheng Kung University | Tainan | 701 | Taiwan |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 26483538 | Background | Kivell TL. Evidence in hand: recent discoveries and the early evolution of human manual manipulation. Philos Trans R Soc Lond B Biol Sci. 2015 Nov 19;370(1682):20150105. doi: 10.1098/rstb.2015.0105. | |
| 24878351 | Background | Vergara M, Sancho-Bru JL, Gracia-Ibanez V, Perez-Gonzalez A. An introductory study of common grasps used by adults during performance of activities of daily living. J Hand Ther. 2014 Jul-Sep;27(3):225-33; quiz 234. doi: 10.1016/j.jht.2014.04.002. Epub 2014 Apr 21. |
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Subjects play the virtual reality game using the wfc input system followed by the wofc input system
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The subjects were informed regarding which input system was to be used
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| 5 minutes |
| Recall | The ability to recall information of each particapant was measured using the forward digit span test at the beginning of the experiment | 5 minutes |
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| 32661649 | Background | Strote C, Golz C, Stroehlein JK, Haase FK, Koester D, Reinsberger C, Vieluf S. Effects of force level and task difficulty on force control performance in elderly people. Exp Brain Res. 2020 Oct;238(10):2179-2188. doi: 10.1007/s00221-020-05864-1. Epub 2020 Jul 13. |
| Background | Howard, M. C. (2017). A meta-analysis and systematic literature review of virtual reality rehabilitation programs. Computers in Human Behavior, 70, 317-327. https://doi.org/10.1016/j.chb.2017.01.013 |
| Background | Pereira, M. F., Prahm, C., Kolbenschlag, J., Oliveira, E., & Rodrigues, N. F. (2020). A Virtual Reality Serious Game for Hand Rehabilitation Therapy. 2020 IEEE 8th International Conference on Serious Games and Applications for Health (SeGAH), 1-7. https://doi.org/10.1109/SeGAH49190.2020.9201789 |
| 29276499 | Background | Vanbellingen T, Filius SJ, Nyffeler T, van Wegen EEH. Usability of Videogame-Based Dexterity Training in the Early Rehabilitation Phase of Stroke Patients: A Pilot Study. Front Neurol. 2017 Dec 8;8:654. doi: 10.3389/fneur.2017.00654. eCollection 2017. |
| 24885076 | Background | Friedman N, Chan V, Reinkensmeyer AN, Beroukhim A, Zambrano GJ, Bachman M, Reinkensmeyer DJ. Retraining and assessing hand movement after stroke using the MusicGlove: comparison with conventional hand therapy and isometric grip training. J Neuroeng Rehabil. 2014 Apr 30;11:76. doi: 10.1186/1743-0003-11-76. |
| 28473763 | Background | Bae SJ, Jang SH, Seo JP, Chang PH. The Optimal Speed for Cortical Activation of Passive Wrist Movements Performed by a Rehabilitation Robot: A Functional NIRS Study. Front Hum Neurosci. 2017 Apr 20;11:194. doi: 10.3389/fnhum.2017.00194. eCollection 2017. |
| 36845877 | Background | Zheng J, Ma Q, He W, Huang Y, Shi P, Li S, Yu H. Cognitive and motor cortex activation during robot-assisted multi-sensory interactive motor rehabilitation training: An fNIRS based pilot study. Front Hum Neurosci. 2023 Feb 9;17:1089276. doi: 10.3389/fnhum.2023.1089276. eCollection 2023. |
| 35500604 | Background | Xia W, Dai R, Xu X, Huai B, Bai Z, Zhang J, Jin M, Niu W. Cortical mapping of active and passive upper limb training in stroke patients and healthy people: A functional near-infrared spectroscopy study. Brain Res. 2022 Aug 1;1788:147935. doi: 10.1016/j.brainres.2022.147935. Epub 2022 Apr 29. |
| Background | Hummel, J., Dodiya, J., Wolff, R., Gerndt, A., & Kuhlen, T. (2013). An evaluation of two simple methods for representing heaviness in immersive virtual environments. 2013 IEEE Symposium on 3D User Interfaces (3DUI), 87-94. https://doi.org/10.1109/3DUI.2013.6550202 |