Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The ONWARDS insulin icodec trials

A round-up of the ONWARDS phase 3 clinical trials evaluating the novel weekly insulin icodec in people with diabetes.
ADVANCED SEARCH
Log in
Top
Journal of NeuroEngineering and Rehabilitation
Published in: Journal of NeuroEngineering and Rehabilitation 1/2017

Open Access 01-12-2017 | Research

Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-concept

Authors: Junkai Xu, Tian Bao, Ung Hee Lee, Catherine Kinnaird, Wendy Carender, Yangjian Huang, Kathleen H. Sienko, Peter B. Shull

Published in: Journal of NeuroEngineering and Rehabilitation | Issue 1/2017

Login to get access

Abstract

Background

Postural balance and gait training is important for treating persons with functional impairments, however current systems are generally not portable and are unable to train different types of movements.

Methods

This paper describes a proof-of-concept design of a configurable, wearable sensing and feedback system for real-time postural balance and gait training targeted for home-based treatments and other portable usage. Sensing and vibrotactile feedback are performed via eight distributed, wireless nodes or “Dots” (size: 22.5 × 20.5 × 15.0 mm, weight: 12.0 g) that can each be configured for sensing and/or feedback according to movement training requirements. In the first experiment, four healthy older adults were trained to reduce medial-lateral (M/L) trunk tilt while performing balance exercises. When trunk tilt deviated too far from vertical (estimated via a sensing Dot on the lower spine), vibrotactile feedback (via feedback Dots placed on the left and right sides of the lower torso) cued participants to move away from the vibration and back toward the vertical no feedback zone to correct their posture. A second experiment was conducted with the same wearable system to train six healthy older adults to alter their foot progression angle in real-time by internally or externally rotating their feet while walking. Foot progression angle was estimated via a sensing Dot adhered to the dorsal side of the foot, and vibrotactile feedback was provided via feedback Dots placed on the medial and lateral sides of the mid-shank cued participants to internally or externally rotate their foot away from vibration.

Results

In the first experiment, the wearable system enabled participants to significantly reduce trunk tilt and increase the amount of time inside the no feedback zone. In the second experiment, all participants were able to adopt new gait patterns of internal and external foot rotation within two minutes of real-time training with the wearable system.

Conclusion

These results suggest that the configurable, wearable sensing and feedback system is portable and effective for different types of real-time human movement training and thus may be suitable for home-based or clinic-based rehabilitation applications.
Literature
1.
Pavlou M, Lingeswaran A, Davies RA, Gresty MA, Bronstein AM. Simulator based rehabilitation in refractory dizziness. J Neurol. 2004;251:983–95.CrossRefPubMed
2.
Jung JY, Kim JS, Chung PS, Woo SH, Rhee CK. Effect of vestibular rehabilitation on dizziness in the elderly. Am J Otolaryngol. 2009;30:295–9.CrossRefPubMed
3.
Shull PB, Silder A, Shultz R, Dragoo JL, Besier TF, Delp SL, Cutkosky MR. Six-week gait retraining program reduces knee adduction moment, reduces pain, and improves function for individuals with medial compartment knee osteoarthritis. J Orthop Res. 2013;31:1020–5.CrossRefPubMed
4.
Simic M, Wrigley TV, Hinman RS, Hunt MA, Bennell KL. Altering foot progression angle in people with medial knee osteoarthritis: the effects of varying toe-in and toe-out angles aremediated by pain and malalignment. Osteoarthr Cartil. 2013;21:1272–80.CrossRefPubMed
5.
Chang A, Hurwitz D, Dunlop D, Song J, Cahue S, Hayes K, Sharma L. The relationship between toe-out angle during gait and progression of medial tibiofemoral osteoarthritis. Ann Rheum Dis. 2007;66:1271–5.CrossRefPubMedPubMedCentral
6.
Dickstein R, Dunsky A, Marcovitz E. Motor imagery for gait rehabilitation in post-stroke hemiparesis. Phys Ther. 2004;84:1167–77.PubMed
7.
Patel S, Park H, Bonato P, Chan L, Rodgers M. A review of wearable sensors and systems with application in rehabilitation. J Neuroeng Rehabil. 2012;9:21.CrossRefPubMedPubMedCentral
8.
Shull PB, Jirattigalachote W, Hunt MA, Cutkosky MR, Delp SL. Quantified self and human movement: a review on the clinical impact of wearable sensing and feedback for gait analysis and intervention. Gait Posture. 2014;40:11–9.CrossRefPubMed
9.
Menguc Y, Park YL, Pei H, Vogt D, Aubin MA, Winchell E, Fluke L, Stirling L, Wood RJ, Walsh CJ. Wearable soft sensing suit for human gait measurement. Int J Robot Res. 2014;33:1748–64.CrossRef
10.
Donath L, Faude O, Lichtenstein E, Nüesch C, Mündermann A. Validity and reliability of a portable gait analysis system for measuring spatiotemporal gait characteristics: comparison to an instrumented treadmill. J Neuroeng Rehabil. 2016;13:6.CrossRefPubMedPubMedCentral
11.
Rodríguez-Martín D, Pérez-López C, Samà A, Cabestany J, Català A. A wearable inertial measurement unit for long-term monitoring in the dependency care area. Sensors. 2013;13:14079–104.CrossRefPubMedPubMedCentral
12.
Guo Y, Zhao G, Liu Q, Mei Z, Ivanov K, Wang L. Balance and knee extensibility evaluation of hemiplegic gait using an inertial body sensor network. Biomed Eng Online. 2013;12:83.CrossRefPubMedPubMedCentral
13.
Motoi K, Taniguchi S, Baek M, Wakugawa M, Sonoda T, Yuji T, Higashi Y, Fujimoto T, Ogawa M, Tanaka S, Yamakoshi KI. Development of a wearable gait monitoring system for evaluating efficacy of walking training in rehabilitation. Sensors Mater. 2012;24:359–73.
14.
15.
Sienko KH, Whitney WJ, Carender WJ, Wall C. The role of sensory augmentation for people with vestibular deficits: real-time balance aid and/or rehabilitation device? J Vestib Res. 2017;27:63–76.CrossRefPubMed
16.
Sigrist R, Rauter G, Riener R, Wolf P. Augmented visual, auditory, haptic, and multimodal feedback in motor learning: a review. Psychon Bull Rev. 2013;20:21–53.CrossRefPubMed
17.
Bark K, Hyman E, Tan F, Cha E, Jax SA, Buxbaum LJ, Kuchenbecker KJ. Effects of vibrotactile feedback on human learning of arm motions. IEEE Trans Neural Syst Rehabil Eng. 2015;23:51–63.CrossRefPubMed
18.
Marchal-Crespo L, Van Raai M, Rauter G, Wolf P, Riener R. The effect of haptic guidance and visual feedback on learning a complex tennis task. Exp Brain Res. 2013;231:277–91.CrossRefPubMed
19.
Lieberman J, Breazeal C. TIKL: development of a wearable Vibrotactile feedback suit for improved human motor learning. IEEE Trans Robot. 2007;23:919–26.CrossRef
20.
Bao T, Carender WJ, Kinnaird C, Barone VJ, Peethambaran G, Kabeto M, Seidler RD, Sienko KH. Effects of home-based balance training with vibrotactile sensory augmentation in community dwelling older adults. In: International Society for Posture and Gait Research; 2017.
21.
Brugnera C, Bittar RSM, Greters ME, Basta D. Effects of vibrotactile vestibular substitution on vestibular rehabilitation - preliminary study. Braz J Otorhinolaryngol. 2015;81:616–21.CrossRefPubMed
22.
Rossi-Izquierdo M, Ernst A, Soto-Varela A, Santos-Perez S, Faraldo-Garcia A, Sesar-Ignacio A, Basta D. Vibrotactile neurofeedback balance training in patients with Parkinson’s disease: reducing the number of falls. Gait Posture. 2013;37:195–200.CrossRefPubMed
23.
Chen KH, Chen PC, Liu KC, Chan CT. Wearable sensor-based rehabilitation exercise assessment for knee osteoarthritis. Sensors (Switzerland). 2015;15:4193–211.CrossRef
24.
Lindeman RW, Yanagida Y, Hosaka K, Abe S. The TactaPack: a wireless sensor/actuator package for physical therapy applications. In: Symposium on haptic interfaces for virtual environment and Teleoperator systems; 2006. p. 337–41.
25.
Reeder RA. Detecting knee hyperextension using goniometric inclinometer sensing with vibrotactile feedback. In: Instrumentation and Measurement Technology Conference Volume, vol. 2; 1998. p. 863–7.
26.
Basta D, Rossi-Izquierdo M, Soto-Varela A, Greters ME, Bittar RS, Steinhagen-Thiessen E, Eckardt R, Harada T, Goto F, Ogawa K, Ernst A: Efficacy of a Vibrotactile neurofeedback training in stance and gait conditions for the treatment of balance deficits: a double-blind, Placebo-Controlled Multicenter Study. Otol Neurotol 2011, 32(January):492–1499.
27.
28.
Gopalai AA, Senanayake SMNA, Member S. A wearable real-time intelligent posture corrective system using Vibrotactile feedback. IEEE Trans Mechatronics. 2011;16:827–34.CrossRef
29.
30.
Kok M, Hol JD, Schön TB, Gustafsson F, Luinge H. Calibration of a magnetometer in combination with inertial sensors. In: International conference on information FUSION (FUSION); 2012. p. 787–93.
31.
Madgwick SOH, Harrison AJL, Vaidyanathan R. Estimation of IMU and MARG orientation using a gradient descent algorithm. IEEE Int Conf Rehabil Robot. 2011:179–185.
32.
Klatt BN, Carender WJ, Lin C. A conceptual framework for the progression of balance exercises in persons with balance and vestibular disorders. Phys Med Rehabil Int. 2015;2:1–8.
33.
Espy D, Nathan C, Tony W, Natalie K. Development of a rating scale for perceived stability during balance training. In: International Society for Posture and Gait Research; 2014.
34.
Sienko KH, Balkwill MD, Oddsson LIE, Wall C. Effects of multi-directional vibrotactile feedback on vestibular-deficient postural performance during continuous multi-directional support surface perturbations. J Vestib Res. 2008;18:273–85.PubMed
35.
Huang Y, Jirattigalachote W, Cutkosky MR, Zhu X, Shull PB. Novel foot progression angle algorithm estimation via foot-worn, magneto-inertial sensing. IEEE Trans Biomed Eng. 2016;63:2278–85.CrossRefPubMed
36.
Haggerty S, Jiang LT, Galecki A, Sienko KH. Effects of biofeedback on secondary-task response time and postural stability in older adults. Gait Posture. 2012;35:523–8.CrossRefPubMedPubMedCentral
37.
van den Noort JC, Steenbrink F, Roeles S, Harlaar J. Real-time visual feedback for gait retraining: toward application in knee osteoarthritis. Med Biol Eng Comput. 2014;53:275–86.CrossRefPubMed
38.
Shull PB, Lurie KL, Cutkosky MR, Besier TF. Training multi-parameter gaits to reduce the knee adduction moment with data-driven models and haptic feedback. J Biomech. 2011;44:1605–9.CrossRefPubMed
39.
Favre J, Aissaoui R, Jolles BM, de Guise JA, Aminian K. Functional calibration procedure for 3D knee joint angle description using inertial sensors. J Biomech. 2009;42:2330–5.CrossRefPubMed
40.
Muller P, Begin M-A, Schauer T, Seel T. Alignment-Free, Self-Calibrating Elbow Angles Measurement using Inertial Sensors. IEEE J Biomed Heal Informatics. 2017;21(2):312–9.CrossRef
41.
O’Donovan KJ, Kamnik R, O’Keeffe DT, Lyons GM. An inertial and magnetic sensor based technique for joint angle measurement. J Biomech. 2007;40:2604–11.CrossRefPubMed
42.
Harrar V, Harris LR. Simultaneity constancy: detecting events with touch and vision. Exp Brain Res. 2005;166:465–73.CrossRefPubMed
43.
Peon AR, Prattichizzo D. Reaction times to constraint violation in haptics: comparing vibration, visual and audio stimuli. World Haptics Conf. 2013:657–61.
44.
Barghout A, Cha J, El SA, Kammerl J, Steinbach E. Spatial resolution of vibrotactile perception on the human forearm when exploiting funneling illusion. 2009 IEEE Int Work Haptic Audio Vis Environ Games, HAVE 2009 - Proc. 2009:19–23.
45.
Van EJBF. Vibrotactile spatial acuity on the torso: effects of location and timing parameters. First Jt Eurohaptics Conf Symp Haptic Interfaces Virtual Environ Teleoperator Syst World Haptics Conf. 2005;0:80–5.
46.
Lederman S. Skin and touch. Encycl Hum Biol. 1997;8:49–61.
47.
Pyo D, Yang TH, Ryu S, Kwon DS. Novel linear impact-resonant actuator for mobile applications. Sensors Actuators A Phys. 2015;233:460–71.CrossRef
48.
Gomez C, Oller J, Paradells J. Overview and evaluation of bluetooth low energy: an emerging low-power wireless technology. Sensors. 2012;12:11734–53.CrossRefPubMedCentral
49.
Chen M, Gonzalez S, Vasilakos A, Cao H, Leung VCM. Body area networks: a survey. Mob Networks Appl. 2011;16:171–93.CrossRef
50.
Banala SK, Kim SH, Agrawal SK, Scholz JP. Robot assisted gait training with active leg exoskeleton (ALEX). Proc 2nd Bienn IEEE/RAS-EMBS Int Conf Biomed Robot Biomechatronics, BioRob. 2008;2008(17):653–8.
51.
52.
Legg L, Langhorne P. Rehabilitation therapy services for stroke patients living at home: systematic review of randomised trials. Lancet. 2004;363:352–6.CrossRefPubMed
53.
Tinetti ME, Baker DI, Gottschalk M, Williams CS, Pollack D, Garrett P, Gill TM, Marottoli RA, Acampora D. Home-based multicomponent rehabilitation program for older persons after hip fracture: a randomized trial. Arch Phys Med Rehabil. 1999;80:916–22.CrossRefPubMed
Metadata
Title
Configurable, wearable sensing and vibrotactile feedback system for real-time postural balance and gait training: proof-of-concept
Authors
Junkai Xu
Tian Bao
Ung Hee Lee
Catherine Kinnaird
Wendy Carender
Yangjian Huang
Kathleen H. Sienko
Peter B. Shull
Publication date
01-12-2017
Publisher
BioMed Central
Published in
Journal of NeuroEngineering and Rehabilitation / Issue 1/2017
Electronic ISSN: 1743-0003
DOI
https://doi.org/10.1186/s12984-017-0313-3

Other articles of this Issue 1/2017

Journal of NeuroEngineering and Rehabilitation 1/2017 Go to the issue

Research

Effect of tDCS stimulation of motor cortex and cerebellum on EEG classification of motor imagery and sensorimotor band power

Research

Gait performance and foot pressure distribution during wearable robot-assisted gait in elderly adults

Research

Brain-Computer Interface application: auditory serial interface to control a two-class motor-imagery-based wheelchair

Research

Identifying predictors for postoperative clinical outcome in lumbar spinal stenosis patients using smart-shoe technology

Research

The role of virtual reality in improving motor performance as revealed by EEG: a randomized clinical trial

Research

Overground vs. treadmill-based robotic gait training to improve seated balance in people with motor-complete spinal cord injury: a case report