BACKGROUND: Increased ankle muscle coactivation during gait represents an adaptation strategy to compensate for postural instability in adults after stroke. Although increased ankle muscle coactivation is correlated with gait disorders in adults after stroke, it remains unclear which physical impairments are the most predictive clinical factors explaining ankle muscle coactivation during gait.
OBJECTIVE: To investigate these physical impairments in adults after stroke using stepwise multiple regression analyses.
METHODS: The magnitude of ankle muscle coactivation during gait was quantified with a coactivation index (CoI) for the first and second double support (DS2), and single support (SS) phases in 44 community-dwelling adults after stroke. Paretic motor function, sensory function, spasticity, ankle muscle strength, and balance ability were evaluated.
RESULTS: The regression analysis revealed that the balance ability and paretic ankle plantarflexor muscle strength were significant factors determining the CoI during the SS phase on the paretic side. For the CoI during the DS2 phase on the paretic side, only the balance ability was selected as a significant factor.
CONCLUSION: Adults with impaired balance ability and paretic ankle muscle weakness after stroke used a compensation strategy of increased ankle muscle coactivation on the paretic side to enhance postural stability during gait.
BohannonR. W. (2007). Muscle strength and muscle training after stroke. J Rehabil Med, 39(1), 14–20.
2.
BohannonR. W, & SmithM. B. (1987). Interrater reliability of a modified Ashworth scale of muscle spasticity. Phys Ther, 67(2), 206–207.
3.
BrandstaterM. E., de BruinH., GowlandC., & ClarkB. M. (1983). Hemiplegic gait: Analysis of temporal variables. Arch Phys Med Rehabil, 64(12), 583–587.
4.
BrunnstromS. (1966). Motor testing procedures in hemiplegia: Based on sequential recovery stages. Phys Ther, 46(4), 357–375.
5.
ChouC. Y., ChienC. W., HsuehI. P., SheuC. F., WangC. H., & HsiehC. L. (2006). Developing a short form of the Berg Balance Scale for people with stroke. Phys Ther, 86(2), 195–204.
6.
ChowJ. W., YablonS. A., & StokicD. S. (2012). Coactivation of ankle muscles during stance phase of gait in patients with lower limb hypertonia after acquired brain injury. Clin Neurophysiol, 123(8), 1599–1605.
7.
DetrembleurC., DierickF., StoquartG., ChantraineF., & LejeuneT. (2003). Energy cost, mechanical work, and efficiency of hemiparetic walking. Gait Posture, 18(2), 47–55.
8.
FalconerK., & WinterD. A. (1985). Quantitative assessment of co-contraction at the ankle joint in walking. Electromyogr Clin Neurophysiol, 25(2-3), 135–149.
9.
Fugl-MeyerA. R., JääsköL., LeymanI., OlssonS., & SteglindS. (1975). The post-stroke hemiplegic patient. 1. a method for evaluation of physical performance. Scand J Rehabil Med, 7(1), 13–31.
10.
GeurtsA. C., de HaartM., van NesI. J., & DuysensJ. (2005). A review of standing balance recovery from stroke. Gait Posture, 22(3), 267–281.
11.
GregsonJ. M., LeathleyM. J., MooreA. P., SmithT. L., SharmaA. K., & WatkinsC. L. (2000). Reliability of measurements of muscle tone and muscle power in stroke patients. Age Ageing, 29(3), 223–228.
12.
KitataniR., OhataK., SakumaK., AgaY., YamakamiN., HashiguchiY., & YamadaS. (2016). Ankle muscle coactivation during gait is decreased immediately after anterior weight shift practice in adults after stroke. Posture, 45, 35–40.
13.
KnutssonE., & RichardsC. (1979). Different types of disturbed motor control in gait of hemiparetic patients. Brain, 102(2), 405–430.
14.
LamontagneA., RichardsC. L., & MalouinF. (2000). Coactivation during gait as an adaptive behavior after stroke. J Electromyogr Kinesiol, 10(6), 407–415.
15.
LinJ. H., HsuehI. P., SheuC. F., & HsiehC. L. (2004). Psychometric properties of the sensory scale of the Fugl-Meyer Assessment in stroke patients. Clin Rehabil, 18(4), 391–397.
16.
LinS. I., HsuL. J., & WangH. C. (2012). Effects of ankle proprioceptive interference on locomotion after stroke. Arch Phys Med Rehabil, 93(6), 1027–1033.
17.
LlewellynM., YangJ. F., & ProchazkaA. (1990). Human H-reflexes are smaller in difficult beam walking than in normal treadmill walking. Exp Brain Res, 83(1), 22–28.
18.
MariS., SerraoM., CasaliC., ConteC., MartinoG., RanavoloA., CoppolaG., DraicchioF., PaduaL., SandriniG., & PierelliF. (2014). Lower limb antagonist muscle co-activation and its relationship with gait parameters in cerebellar ataxia. Cerebellum, 13(2), 226–236.
19.
NadeauS., ArsenaultA. B., GravelD., & BourbonnaisD. (1999). Analysis of the clinical factors determining natural and maximal gait speeds in adults with a stroke. Am J Phys Med Rehabil, 78(2), 123–130.
20.
NadeauS., GravelD., ArsenaultA. B., & BourbonnaisD. (1999). Plantarflexor weakness as a limiting factor of gait speed in stroke subjects and the compensating role of hip flexors. Clin Biomech (Bristol, Avon), 14(2), 125–135.
21.
RosaM. C., MarquesA., DemainS., & MetcalfC. D. (2014). Lower limb co-contraction during walking in subjects with stroke: A systematic review. J Electromyogr Kinesiol, 24(1), 1–10.
22.
RosaM. C., MarquesA., DemainS., MetcalfC. D., & RodriguesJ. (2014). Methodologies to assess muscleco-contraction during gait in people with neurological impairment - a systematic literature review. J Electromyogr Kinesiol, 24(2), 179–191.
23.
RueterboriesJ., SpaichE. G., LarsenB., & AndersenO. K. (2010). Methods for gait event detection and analysis in ambulatory systems. Med Eng Phys, 32(6), 545–552.
24.
ShahS. K. (1984). Reliability of the original brunnstrom recovery scale following hemiplegia. Australian Occupational Therapy Journal, 31(4), 144–151.
25.
ShiaviR., BugleH. J., & LimbirdT. (1987). Electromyographic gait assessment, Part 2: Preliminary assessment of hemiparetic synergy patterns. J Rehabil Res Dev, 24(2), 24–30.
26.
SrivastavaA., TalyA. B., GuptaA., KumarS., & MuraliT. (2009). Post-stroke balance training: Role of force platform with visual feedback technique. J Neurol Sci, 287(1-2), 89–93.
27.
TuckerM. G., KavanaghJ. J., BarrettR. S., & MorrisonS. (2008). Age-related differences in postural reaction time and coordination during voluntary sway movements. Hum Mov Sci, 27(5), 728–737.
28.
YangJ. F., & WinterD. A. (1984). Electromyographic amplitude normalization methods: Improving their sensitivity as diagnostic tools in gait analysis. Arch Phys Med Rehabil, 65(9), 517–521.
