Virtual reality (VR) allows visuotactile interaction in a virtual environment. VR has several potential applications such as surgical training, phobia treatments, and gait rehabilitation. However, further interface development is required. Therefore, the objective of this study was to develop a noninvasive wearable device control to a VR gait training program. It consists of custom-made insoles with vibratory actuators, and plantar pressure sensor-based wireless interface with a VR game. System usability testing involved a habituation period and three gaming sessions. Significant gait improvement was associated with game scores (P < 0.05). This VR gait training system allowed real-time virtual immersive interaction with anticipatory stimulus and feedback during gait.
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References
1.
ShinJH, RyuH, JangSH. A task-specific interactive game-based virtual reality rehabilitation system for patients with stroke: A usability test and two clinical experiments. J Neuroeng Rehabil, 2014; (1):1–10; doi: 10.1186/1743-0003-11-32.
2.
BorregoA, LatorreJ, LlorensR, et al.Feasibility of a walking virtual reality system for rehabilitation: Objective and subjective parameters. J Neuroeng Rehabil, 2016; 13:68; doi: 10.1186/s12984-016-0174-1
3.
SantosLF, ChristO, MateK, et al.Movement visualisation in virtual reality rehabilitation of the lower limb: A systematic review. Biomed Eng Online, 2016; 15(3):75–88; doi: 10.1186/s12938-016-0289-4
4.
Matamala-GomezM, MaistoM, MontanaJI, et al.The role of engagement in teleneurorehabilitation: A systematic review. Front Neurol, 2020; 11:354; doi: 10.3389/fneur.2020.00354
5.
ShokurS, GalloS, MoioliRC, et al.Assimilation of virtual legs and perception of floor texture by complete paraplegic patients receiving artificial tactile feedback. Sci Rep, 2016; 6(1):1–14; doi: 10.1038/srep32293
6.
RabuettiM, ScaleraGM, FerrarinM.Effects of gait strategy and speed on regularity of locomotion assessed in healthy subjects using a multi-sensor method, Sensors, 2019; 19(3):513; doi: 10.3390/s19030513
7.
ErtanH, BayramI. Fundamentals of human movement, its control and energetics. Comp Kinesiol Hum Body, 2020; 29–45; doi: 10.1016/B978-0-12-812162-7.00003-5
8.
TuncaC, PehlivanN, AkN, et al.Inertial sensor-based robust gait analysis in non-hospital settings for neurological disorders. Sensors, 2017; 17(4):825; doi: 10.3390/s17040825
9.
Cano-De-La-CuerdaR, Molero-SánchezA, Carratalá-TejadaM, et al.Theories and control models and motor learning: Clinical applications in neurorehabilitation. Neurología, 2015; 30(1):32–41; doi: 10.1016/j.nrleng.2011.12.012
10.
Gómez-JordanaLI, StaordJ, PeperCLE, et al.Virtual footprints can improve walking performance in people with Parkinson's disease. Front Neurol, 2018; 9:681; doi: 10.3389/fneur.2018.00681
11.
HiraokaK, KunimuraH, OdaH, et al.Rhythmic movement and rhythmic auditory cues enhance anticipatory postural adjustment of gait initiation. Somatosens Motor Res, 2020; 37(3):213–221; doi: 10.1080/08990220.2020.1777959
12.
CharltonJM, EngJJ, LiLC, et al.Learning gait modifications for musculoskeletal rehabilitation: Applying motor learning principles to improve research and clinical implementation. Phys Ther, 2021; 101(2):pzaa207; doi: 10.1093/ptj/pzaa207
13.
WatanabeJ, AndoH. Pace-sync shoes: intuitive walking-pace guidance based on cyclic vibro-tactile stimulation for the foot. Virtual Reality, 2010; 14(3):213–219; doi: 10.1007/s10055-009-0137-y
14.
AsqueCT, DayAM, LaycockSD. Augmenting graphical user interfaces with haptic assistance for motion-impaired operators. Int J Hum-Comput Stud, 2014; 72(10–11):689–703; doi: 10.1016/j.ijhcs.2014.05.007
15.
MaCZ-H, WanAH-P, WongDW-C, et al.A vibrotactile and plantar force measurement-based biofeedback system: Paving the way towards wearable balance-improving devices, Sensors, 2015; 15(12) 31709–31722; doi: 10.3390/s151229883
16.
SigristR, RauterG, RienerR, et al.Augmented visual, auditory, haptic, and multimodal feedback in motor learning: A review. Psychonomic Bull Rev, 2013; 20(1):21–53; doi: 10.3758/s13423-012-0333-8
MaculewiczJ, ErkutC, SerafinS. An investigation on the impact of auditory and haptic feedback on rhythmic walking interactions. Int J Hum Comput Stud, 2016; 85:40–46; doi: 10.1016/j.ijhcs.2015.07.003
19.
ChienJH, AmbatiVP, HuangC-K, et al.Tactile stimuli affect long-range correlations of stride interval and stride length differently during walking. Exp Brain Res, 2017; 235(4):1185–1193; doi: 10.1007/s00221-017-4881-z
20.
ShidelerBL, MartelliD, PradoA, et al.Overground gait training using virtual reality aimed at gait symmetry. Hum Movement Sci, 2021; 76:102770; doi: 10.1016/j.humov.2021.102770
21.
JanehO, FründtO, SchönwaldB, et al.Gait training in virtual reality: Short-term effects of different virtual manipulation techniques in Parkinson's disease. Cells, 2019; 8(5):419; doi: 10.3390/cells8050419
22.
DíazS, StephensonJ, LabradorM. Use of wearable sensor technology in gait, balance, and range of motion analysis. Appl Sci, 2019; 10(1):234; doi: 10.3390/app10010234
23.
LiuX, ZhaoC, ZhengB, et al.Wearable devices for gait analysis in intelligent healthcare. Front Comput Sci, 2021; 3; doi: 10.3389/fcomp.2021.661676
24.
LiW, LuW, ShaX, et al.Wearable gait recognition systems based on MEMS pressure and inertial sensors: A Review. IEEE Sens J, 2022; 22(2):1092–1104.
25.
ShuL, HuaT, WangY, et al.In-shoe plantar pressure measurement and analysis system based on fabric pressure sensing array. IEEE Trans Inf Technol Biomed, 2010; 14(3)767–775; doi: 10.1109/TITB.2009.2038904
26.
ShonoH, MatsumotoY, KokubunT, et al.Determination of relationship between foot arch, hindfoot, and hallux motion using Oxford foot model: Comparison between walking and running. Gait Posture, 2022; 92:96–102; doi: 10.1016/j.gaitpost.2021.10.043
27.
SilvaPM, HolandaLJ, GranadosEE, et al.Building pressure-sensitive foot insoles for public health evaluation in smart cities. In: 2017 IEEE First Summer School on Smart Cities (S3C). IEEE, 2017; pp. 153–156; doi: 10.1109/S3C.2017.8501375
28.
ShahK, SolanM, DaweE. The gait cycle and its variations with disease and injury. Orthop Trauma, 2020; 34(3):153–160; doi: 10.1016/j.mporth.2020.03.009
29.
JandováS. Laterality of lower limb and plantar pressure symmetry while walking in young adults. J Hum Sport Exerc, 2019; 14; doi: 10.14198/jhse.2019.144.12
30.
SchlerfJE, GaleaJM, SpampinatoD, et al.Laterality differences in cerebellar–motor cortex connectivity. Cereb Cortex, 2015; 25(7):1827–1834; doi: 10.1093/cercor/bht422
31.
KowalskiE, CatelliDS, LamontagneM. Side does not matter in healthy young and older individuals–examining the importance of how we match limbs during gait studies. Gait Posture, 2019; 67:133–136; doi: 10.1016/j.gaitpost.2018.10.008
32.
van GelderLM, BarnesA, WheatJS, et al.The use of biofeedback for gait retraining: A mapping review. Clin Biomech, 2018; 59:159–166; doi: 10.1016/j.clinbiomech.2018.09.020
33.
AshooriA, EaglemanDM, JankovicJ. Effects of auditory rhythm and music on gait disturbances in Parkinson's disease. Front Neurol, 2015; 6234; doi: 10.3389/fneur.2015.00234
34.
LiuL, SanganiS, PattersonK, et al.Real-time avatar-based feedback to enhance the symmetry of spatiotemporal parameters after stroke: Instantaneous effects of different avatar views. IEEE Trans Neural Syst Rehabil Eng, 2020; 28(4)878–887; doi: 10.1109/TNSRE.2020.2979830
35.
SpeddenME, ChoiJT, NielsenJB, et al.Corticospinal control of normal and visually guided gait in healthy older and younger adults. Neurobiol Aging, 2019; 78:29–41; doi: 10.1016/j.neurobiolaging.2019.02.005
36.
BozgeyikliE, RaijA, KatkooriS, et al.Locomotion in virtual reality for room scale tracked areas. Int J Hum Comput Stud, 2019; 122:38–49; doi: 10.1016/j.ijhcs.2018.08.002
37.
HorsakB, SimonlehnerM, SchöfferL, et al.Overground walking in a fully immersive virtual reality: A comprehensive study on the effects on full-body walking biomechanics. Front Bioeng Biotechnol, 2021; 9:780314; doi: 10.3389/fbioe.2021.780314
38.
YamagamiM, ImsdahlS, LindgrenK, et al.Effects of virtual reality environments on overground walking in people with Parkinson disease and freezing of gait. Disabil Rehabil Assist Technol, 2020:1–8; doi: 10.1080/17483107.2020.1842920
39.
OsabaMY, MartelliD, PradoA, et al.Age-related differences in gait adaptations during overground walking with and without visual perturbations using a virtual reality headset. Sci Rep, 2020; 10(1):1–10; doi: 10.1038/s41598-020-72408-6
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