Effectiveness of backward walking with functional electrical stimulation on the rectus femoris and tibialis anterior for patients with chronic stroke

Abstract

BACKGROUND:

Backward walking is considered as a newly rising method used to enhance gait abilities, but evidence remains unclear.

OBJECTIVE:

To identify whether backward walking with functional electrical stimulation (FES) triggered by a foot switch on the rectus femoris and tibialis anterior could be effective in improving gait parameters of stroke survivors.

METHODS:

This was a cross-sectional study that included fourteen subjects with chronic stroke. Three walking conditions were performed at random: backward walking with FES attached onto the rectus femoris and tibialis anterior (RF+TA), backward walking with FES attached onto the tibialis anterior (TA only), and without electrical intervention (non-FES). The Zebris was used to assess the spatiotemporal gait parameters. Each condition was measured three times and the average value was used for analysis.

RESULTS:

Results showed significant increases in gait speed, cadence, step length, mid-stance percentage, maximal force in the affected midfoot (p < 0.05), and significant decreases in the double stance phase in the RF+TA condition compared to the TA only and the non-FES conditions (p < 0.05).

CONCLUSION:

Functional electrical stimulation to the rectus femoris and tibialis anterior during backward walking could be a clinically effective method to improve gait ability of stroke survivors.

Keywords

Electrical stimulation gait rehabilitation stroke walking ability

1 Introduction

Walking ability is closely related to one’s ability to have an independent daily life (Wang, 2018). However, those affected by stroke have difficulty moving and supporting their weight onto the affected side due to factors such as impaired muscle strength, sensation, visual recognition, and balance (Tyson et al., 2013). Furthermore, weakness of the dorsiflexor muscles result in foot drop, which is a main problem leading to abnormal gait because it causes an ankle strategy failure and a decrease in the swing phase of the gait cycle (Cho & Kim, 2015). For these reasons, gait parameters such as gait speed, step length, and symmetrical ratio of the lower extremities are reduced in patients with stroke, and consequently their independence is limited. Therefore, most patients with stroke aim to perform achieve independence by having better gait abilities (Wang, 2018).

Backward walking provides improvement in gait function and balance in stroke patients and builds confidence in walking (Chen, 2020; Dorian, 2018). Although some studies showed that backward walking is a mirror image of forward walking, backward walking is not a simple reversal of forward walking in those affected by stroke (Balasukumaran et al., 2020). Backward walking requires toe contact instead of heel contact, and relies more on their senses other than the visual system because their vision is limited during backward walking (Balasukumaran et al., 2019; Hoogkamer, 2014). For these reasons, backward walking requires high metabolic costs, and stimulates activation of the sensorimotor system (Hoogkamer, 2014). The activation of the quadriceps muscle is remarkable as a biomechanical advantage during backward walking, which has been used for orthopedic rehabilitation by reducing the mechanical burden on the knee joint (Flynn, 1993). In addition, posterior gait training may produce more improvements in balance and sit to stand abilities, which are factors correlated with falls during daily life activity performance in patients with stroke (Dorian, 2018). It may also be more closely related to the improvement of gait speed, stride length, and gait symmetry compared to forward gait training (Yang, 2005).

In patients with stroke, the application of functional electrical stimulation (FES) corresponding to the gait cycle increases lower extremity muscle strength, gait speed, step length, cadence, etc., and decreases the double stance phase (Cho & Kim, 2015). FES is a treatment method that has proven its effectiveness in reducing stiffness and improving muscle contraction by applying electrical stimulation to muscles and nerves (Sivaramakrishnan et al., 2018; Sharif & Ghulam, 2017). FES applied to patients with stroke who have decreased ankle dorsiflexion is effective in the treatment and prevention of foot drop, and improves walking ability by activating dorsiflexion and eversion in the swing phase (Sabut, 2010; Kottink, 2008). In addition, the application of FES on the gluteus medius muscle, which provides hip stability in the stance phase, and the application of FES of the dorsiflexor muscle in the swing phase showed positive improvement compared to the previous studies that have applied only to the tibialis anterior muscle (Kim, 2012). The effect of FES application and backward walking according to the gait cycle in stroke survivors is well known. However, although the effects of backward walking training has been investigated in previous studies, the inclusion of FES with backward walking training in persons affected by stroke are lacking. Therefore, the aim of this study was to examine the feasibility of improving gait parameters through the application of FES onto the rectus femoris and tibialis anterior muscles during backward walking in stroke survivors.

2 Methods

2.1 Study design

This was a cross-sectional study. After the participants were provided with all the relevant information that they needed in order to decide if they would like to participate in the study, each participant had provided their written informed consent prior to data collection. This research was approved by the Institutional Review Board of Sahmyook University (2-1040781-A-N-012021087HR). The data of the study were collected between July 2021 and September 2021.

2.2 Participants

Fourteen patients with chronic stroke were recruited from the Jang-an Dong Rehabilitation Centers in Dongdaemun-gu, Seoul, Republic of Korea. The inclusion criteria were as follows: (1) diagnosis of first onset of hemiparetic stroke over 6 months ago and no other neurological disease; (2) no orthopedic or neurological histories affecting gait performances; (3) manual muscle test (MMT) grade under P+(2+) in the RF and TA muscles, which indicates that movement through partial ROM against gravity or movement through complete ROM in a gravity-eliminated position with resistance was possible, and the ability to walk at least 10 m without any assistance; (4) a Mini Mental State Examination (MMSE) score of over 24 to ensure that the participants had adequate cognitive ability to communicate and follow instructions. Patients who had difficulties with backward walking or had vestibular or cerebellar diseases were excluded. All subjects were evaluated and screened using the criteria of inclusion and exclusion.

To determine the minimum number of subjects, G*power 3.1 version was used. The sample size was estimated with a given effect size of 0.5, statistical power of 0.8, and significance level of (α) 0.05 using the F-test (repeated measure ANOVA). The sample size of 14 was determined, and it considered a 20% dropout rate.

2.3 Equipment and data collection

Functional electrical stimulation (EMG-FES 3000, Cyber Medic Inc., Iksan, Republic of Korea, 2009) was attached onto the rectus femoris and tibialis anterior muscles. The parameters used for muscle activation were a symmetrical biphasic waveform with a frequency of 40 Hz and a pulse width of 200 μ. The intensity was increased enough to elicit dorsiflexion and knee extension without pain.

The Zebris system (Zebris FDM 1.5 platform, GmbH, Germany) assessed the spatiotemporal parameters such as gait velocity, cadence, stride length, mid-stance percentage, and double stance phase. In addition, this device which consists of 11264 pressure sensors could measure kinetic parameters such as maximal force and maximal pressure of the affected side. Intuitive software automatically calculated the standard gait parameters when subjects walked on the Zebris system with a sample rate of 100 Hz (Van Alsenoy, 2019). When the device analyzed the subjects in standing position, the load produced from the body was displayed as a bar chart and as numerical data. They provided immediate information about load distribution through lines connecting to the main points of the body. Collected data was recorded over a specified period of time and the results are averaged. This study analyzed the force and pressure of the load as averaged data.

Backward walking speed was measured with the 3 m backward walking test. Carter et al. (2019) reported in a recent study that backward walking is more sensitive to age-related changes in mobility and balance compared with forward walking. Cronbach’s alpha is a method of evaluating reliability by comparing the amount of shared variance, or covariance. Intra-class correlation coefficient (ICC) is the assessment of consistency of quantitative measures which are traced by different observers measuring the same quantity. The reliability of internal consistency of the 3 m backward walking test was 0.974 in the Cronbach’s alpha and the ICC was 0.985 (Kocaman, 2021). An ICC value is considered as poor if its value is less than 0.5, as moderate if its value is between 0.5 and 0.75, as good if its value is between 0.75 and 0.9, and as excellent if its value is higher than 0.9 (Koo & Lee, 2016). Thus, the 3 m backward walking test was highly reliable and useful for analyzing the effects of backward walking in patients affected by stroke (Kocaman, 2021).

2.4 Procedures and Intervention

Functional electrical stimulation electrodes (EMG-FES 3000, Cyber Medic Inc., Iksan, Republic of Korea, 2009) were attached onto the rectus femoris and tibialis anterior muscles. Each participant was measured under three conditions using the FES and a foot switch while participants walked on a Zebris system (Zebris Medical, GmbH, Germany): (1) backward walking with the FES attached onto the rectus femoris and tibialis anterior (RF+TA), (2) backward walking with the FES attached onto the tibialis anterior (TA only), (3) backward walking without any electrical intervention (non-FES).

The rectus femoris electrode was placed horizontally at approximately two finger widths above the knee, and another electrode was placed at a minimum of two finger widths apart centered in the muscle belly. The electrode on the tibialis anterior was placed on the muscle belly between the tibial tuberosity and the fibular head, and another electrode was placed approximately two-thirds of the way down the shin with the leads facing toward the midline of the body (Figure 1).

Fig. 1

FES electrode placement on the rectus femoris (RF) and tibialis anterior (TA) during backward walking.

Before conducting a test, participants were asked to walk backwards according to their walking ability several times in order to familiarize themselves with the FES. The FES was activated by a foot switch attached to the subject’s forefoot. When the forefoot on the affected side contacted the floor, the rectus femoris was activated. The tibialis anterior was activated when the forefoot detached the floor, reciprocally.

All participants performed backward walking at the comfortable speed down a three-meter walkway. Despite the permission of the mobility aids such as canes, prosthetic devices, and orthotic devices, no one used them. The participants were randomized into three conditions by drawing lots for every trial and were evaluated by an assessor who was blinded to condition allocations. The therapist provided standby assist for safety reasons and to prevent participants from falling. The average value was measured three times for each condition and was used for analysis. To reduce any possible side effects of muscle soreness or fatigue, the subjects were provided with a 1-minute rest period between each condition. Since this was a cross-sectional study, there were no missing data.

2.5 Outcome measures

The general characteristics of participants were measured prior to the assessment. The dependent variables were the gait parameters (gait velocity, cadence, stride length, mid-stance percentage, double stance phase), and kinetic data (maximal force, maximal pressure). Appropriateness of the repeated measures analysis was confirmed by the Mauchly Sphericity Test. The effect sizes of the outcome measures were calculated in terms of Cohen’s f. This study revealed a large effect size for gait velocity, cadence, stride length, mid-stance percentage, double stance phase, and maximal force. The increase in gait velocity constituted an effect size of f = 1.32. The increase in cadence constituted an effect size of f = 1.04. The increase in stride length constituted an effect size of f = 1.50. The increase in mid-stance percentage constituted an effect size of f = 1.13. The increase in double stance phase constituted an effect size of f = 1.44. The increase in maximal force of the affected side constituted an effect size of f = 0.82.

2.6 Statistics

Predictive Analytics SoftWare (PASW) for Windows Version 20.0 (IBM Co., Armonk, NY, USA) was used for statistical analysis in this study. To confirm for normality, the Shapiro-Wilk test was used. The one-way repeated measures ANOVA was used to determine the effects of backward walking according to the FES conditions (RF+TA, TA only and non-FES conditions).

3 Results

The general characteristics of the subjects are shown in Table 1. There were significant increases in gait velocity, cadence, stride length, mid-stance percentage, and significant decreases in the double stance phase in the RF+TA condition compared to the TA only and the non-FES conditions (Tables 2). In addition, the spatiotemporal parameters showed the same tendency in TA only condition compared to the non-FES condition.

Table 1
General characteristics of subjects (N = 14)

Subjects

Gender (M/F) 14/0

Age (yrs) 60.9±10.7^a

Height (cm) 169.1±5.8

Weight (kg) 64.3±11.6

Stroke duration (months) 39.3±23.4

Cause (infarction/hemorrhage) 9/5

Affected side (right/left) 5/9

	Subjects
Gender (M/F)	14/0
Age (yrs)	60.9±10.7^a
Height (cm)	169.1±5.8
Weight (kg)	64.3±11.6
Stroke duration (months)	39.3±23.4
Cause (infarction/hemorrhage)	9/5
Affected side (right/left)	5/9

^aMean±standard deviation.

Table 2

Changes in gait spatiotemporal parameters according to FES application sites (N = 14)

Item	RF+TA	TA only	Non-FES	F(p)
Gait velocity (cm/s)	24.08±12.60^*†	19.45±10.01^*	14.98±7.32^a	22.823(<0.001)
Cadence (step/min)	71.36±31.12^*†	67.26±28.42^*	61.60±26.90	14.087(<0.01)
Stride length (cm)	39.71±11.26^*†	35.07±10.09^*	30.74±10.07	32.092(<0.001)
Midstance (% cycle)
Affected side	21.45±6.95^*†	19.04±6.51^*	16.27±6.46	16.551(<0.001)
Less affected side	25.41±6.01^*†	24.09±6.56^*	21.97±6.64	12.724(<0.001)
Double stance phase (% cycle)	53.55±12.29^*†	57.39±12.54^*	62.31±12.18	26.872(<0.001)

RF+TA = Backward walking with FES on RA and TA; TA = Backward walking with FES on TA only; Non-FES: Normal backward walking with no FES. ^aMean±standard deviation. ^† Significantly different from TA only (p < 0.05). ^* Significantly different from Non-FES (p < 0.05).

The maximal force in the affected side was significantly increased in the RF+TA condition compared to the TA only and the non-FES conditions, and it was significantly increased in the TA only compared to non-FES condition. In the RF+TA condition, however, there were no differences in the maximal force of the less affected side compared with the TA only and non-FES conditions. There were also no differences in the maximal force of the less affected side between the TA only and non-FES conditions. There were no significant differences in maximal pressure on both sides in the RF+TA, TA only, and non-FES conditions (Table 3).

Table 3

Variation of maximum force and pressure according to FES application sites (N=14)

Item	RF+TA	TA only	Non-FES	F(p)
Maximum force (N)
Affected side	218.30±82.18^*†	200.76±82.52^*	189.84±88.97	8.688(<0.05)
Less affected side	296.02±109.03	290.34±108.48	274.44±100.98	2.316(0.081)
Maximum pressure (N/cm²)
Affected side	16.24±9.70	14.50±7.51	14.60±10.00	2.862(0.118)
Less affected side	21.02±8.91	18.78±6.35	17.89±6.49	5.973(0.080)

RF+TA = Backward walking with FES on RA and TA; TA = Backward walking with FES on TA only; Non-FES: Normal walking with no FES. ^aMean±standard deviation. ^† Significantly different from TA only (p < 0.05). ^* Significantly different from Non-FES (p < 0.05).

4 Discussion

This study identified whether backward walking with FES triggered by a foot switch on the rectus femoris and tibialis anterior could be effective in increasing the gait parameters of patients with chronic stroke. The results of this study demonstrated that backward walking with FES on the rectus femoris and tibialis anterior was effective in improving maximal force and gait parameters including gait velocity, cadence, stride length, mid-stance percentage, and double stance phase. Accordingly, several significant findings were as follows: First, gait parameters in the RF+TA condition such as gait velocity, cadence, and stride length was significantly greater than in the other conditions. Second, the maximal force on the affected side in the RF+TA condition was significantly improved than in the other conditions. Finally, the improvement of gait symmetry in the RF+TA condition was superior to that of other conditions (effect size of f > 0.40, as a large effect). Second, the mid-stance percentage in the affected side was significantly increased in the other conditions (effect size of f > 0.40, as a large effect). Finally, the maximal force on the affected side in the RF+TA condition was significantly improved than in the other conditions (effect size of f > 0.40, as a large effect). This result indicates that the use of FES on the rectus femoris and tibialis anterior has potential in improving the gait ability.

Kinematic and kinetic studies showed that the pattern of vertical ground reaction force (GRF) curves were different between forward walking and backward walking. In forward walking, GRF showed a first peak for the loading response and a second peak for propulsion, and the two peaks were approximately symmetrical. However, in backward walking, the first peak due to the loading response was always higher than the second peak due to propulsion. Therefore, in the backward walking, a plateau shape was observed in the pre-swing stage (Lee, 2013). These results indicated the importance of muscle activation to the load response when walking backwards. According to previous studies, the knee extensor muscles, such as the vastus lateralis and rectus femoris, were activated from the initial contact to the terminal stance phase (Winter, 1989). This activation forced the knee to remain in extension to prevent the body’s center of mass from dropping during the stance phase of backward walking (Threlkeld, 1989). Several papers on backward walking particularly focused on the rectus femoris, which can produce the greatest force and have good muscular endurance (Kim et al., 2016). Thus, the improvement of rectus femoris muscle strength enables the affected knee joint to support the body weight, approaching the ideal gait cycle, and ultimately improving the gait parameters such as gait velocity, stride length, and cadence.

Functional electrical stimulation has been widely used in the rehabilitation field for the purpose of restoring motor function and preventing muscle strength loss in patients with neurological diseases such as stroke and spinal cord injury (Kapadia, 2020). Repetitive and continuous signaling of FES can lead to changes in the synapse between upper motor neurons and alpha motor neurons according to the principle of neuroplasticity (McGie, 2015). In addition, FES applied to patients with chronic stroke improved somatosensory activities and functional movements, and FES applied with exercise promoted motor learning by activating the paretic sides (Hara, 2008). In particular, there were many studies which have demonstrated the effectiveness of FES applied to the muscles in accordance with the gait cycle (Howlett, 2015).

Instability of the mid stance and decreased dorsiflexion can cause gait disturbances in stroke survivors (Kim, 2012). In stroke survivors, weight bearing and weight shifting on the affected side are considered an important goal in functional gait. Failure to put weight on the lower extremities while walking negatively affects independent gait and balance recovery. Knee extensor is important during backward walking to maintain the position of the lower extremities on the affected side by prolonged activation. In particular, the rectus femoris is the main part of the single support phase to ensure stability of the affected side (Thorstensson, 1986).

Foot drop is a condition, which is representing a sign of the neuromuscular damage caused by the weakness of the tibialis anterior in post stroke patients. Due to weakness of the tibialis anterior, ankle joint fails to produce propulsion during the stance phase and reduce clearance during swing phase. To solve these problem, FES on the tibialis anterior is very commonly used in correction foot drop in poststroke patients (Sabut et al., 2013).

For these reasons, in this study, FES applied to the rectus femoris and tibialis anterior muscles was adopted as an intervention method to offset the decrease in stability in the stance phase and foot drop in the swing phase due to muscle weakness on the affected side in stroke survivors, and the authors confirmed the effectiveness of the backward walking.

Many researchers have conducted studies to prove the correlation between the spatiotemporal parameters and force. A recent study demonstrated a linear correlation between gait velocity and propulsion in patients with stroke. In particular, gait velocity is explained by the combination of cadence and propulsion which is consistent with our findings (Hsiao, 2016). In our study, the maximal force of the forefoot, which represented the ground reaction force, was significantly increased in the RF+TA conditions compared to the other conditions, and it was increased in the TA only conditions compared to the general backward walking conditions. These results indicate that FES applied to the rectus femoris increased the stability of the stance phase by promoting weight bearing and weight shifting in the affected lower extremity.

There are some things to be cautious with when implementing a backward walking program for stroke patients in clinical practice. First, since most stroke survivors have little experience with backward walking after injury, they should be guided with sufficient time before exercise. Second, excessive FES application and backward walking causes local muscle fatigue and delayed onset muscle soreness, so it is necessary to stretch the lower extremity muscles before and after exercise (Myatt, 1995). Flynn (1994) reported that the maximum oxygen intake, heart rate, and blood lactic acid concentration were higher than that of forward walking, and that it was necessary to check the physical condition required for backward walking training.

Since this study verified only the temporary effects of FES on backward walking with a cross-sectional study design, an experimental study to verify the long-term effects of FES on the rectus femoris and tibialis anterior muscles is needed in the future. In addition, it is difficult to generalize these findings because the sample size was small and all gait variables could not be measured. Therefore, further studies are warranted to confirm the beneficial effects of backward walking training on the examined dependent variables in not only the stroke survivors but in other neurological disorders as well that affect gait.

5 Conclusion

This study showed that the attachment of functional electrical stimulation to the rectus femoris and tibialis anterior muscles during backward walking could clinically be an effective intervention in improving gait performance of patients with chronic stroke.

Conflict of interest

The authors have no conflict of interest to report.

Footnotes

Acknowledgments

The study was supported by Sahmyook University (2021).

Funding

The authors report no funding.

References

Balasukumaran Tharani , Gottlieb Uri , Springer Shmuel (2020) Spatiotemporal gait characteristics and ankle kinematics of backward walking in people with chronic ankle stability, Scientific Reports 10, 11515.

Balasukumaran Tharani , Oliver Benita , Ntsiea Mokgobadibe Veronica , (2019) The effectiveness of backward walking as a treatment for people with gait impairments: a systematic review and meta-analysis, Clinical Rehabilitation 33(2), 171–182.

Carter Valeri , Jain Tarang , Cornwall Mark , (2019) The 3-m backwards walk and reptrospective falls: diagnostic accuracy of a novel clinical measure, Journal of Geriatric Physical Therapy 42(4), 249–255.

Chen Ze-Hua , Ye Xiang-Ling , Chen Wei-Jian , Chen Guo-Qian , Wu Jia-Tao , Xu Xue-Meng , (2020) Effectiveness of backward walking for people affected by stroke: A systematic review and meta-analysis of randomized controlled trials.e, Medicine (Baltimore) 99(27), 20731.

Cho Min-Kwon , Kim Jung-Hyun , (2015) Treadmill gait training combined with functional electrical stimulation on hip abductor and ankle dorsiflexor muscles for chronic hemiparesis, Gait & Posture 42(1), 73–78.

Dorian,

R. K.

(2018) A backward walking training program to improve balance and mobility in acute stroke: a pilot randomized controlled trial, Journal of Neurologic Physical Therapy 42(1), 12–21.

Flynn,

T. W.

(1993) Mechanical power and muscle action during forward and backward running, Journal of Orthopaedic and Sports Physical Therapy 17(2), 108–12.

Flynn,

T. W.

(1994) Comparison of cardiopulmonary responses to forward and backward walking and running, Medicine and Science in Sports and Exercise 26(1), 89–94.

Hara Yukihiro , Ogawa Shinji , Tsujiuchi Kazuhito , Muraoka Yoshihiro , (2008) A home— based rehabilitation program for the hemiplegic upper extremity by power-assisted functional electrical stimulation, Disability and Rehabilitation 30(40), 296–304.

10.

Hoogkamer Wouter (2014) Steps forward in understanding backward gait: from basic circuits to rehabilitation, Exercise and Sports Sciences Reviews 42(1), 23–29.

11.

Howlett Owen

(2015) Functional electrical stimulation improves activity after stroke: a systematic review with meta-analysis, Archives of Physical Medicine Rehabilitation 96(5), 934–943.

12.

Hsiao HaoYuan (2016) Evaluation of measurements of propulsion used to reflect changes in walking speed in individuals poststroke, Journal of Biomechanical Engineering 49(16), 4107–4112.

13.

Kapadia Naaz , Moineau Bastien (2020) Functional electrical stimulation therapy for retraining reaching and grasping after spinal cord injury and stroke, Frontiers in Neuroscience 14(718).

14.

Kim Jung-Hyun (2012) Functional electrical stimulation applied to gluteus medius and tibialis anterior corresponding gait cycle for stroke, Gait & Posture 36(1), 65–67.

15.

Kim Won-Hyo , Kim Won-Bok , Yun Chang-Kyo (2016) The effects of forward and backward walking according to treadmill inclination in children with cerebral palsy, Journal of Physical Therapy Science 28(5), 1569–1573.

16.

Kocaman Ayse Abit (2021) Validity and reliability of the 3-meter backward walk test in individuals with stroke, Journal of Stroke and Cerebrovasccular Diseases 30(1), 105462.

17.

Koo Terry

, Li Mae,

(2016) A Guideline of Selecting and Reporting Intraclass Correlation Coefficients for Reliability Research, Journal of Chiropractic Medicine 15(2), 155–163.

18.

Kottink Anke

I. R.

(2008) Therapeutic effect of an implantable peroneal nerve stimulator in subjects with chronic stroke and footdrop: a randomized controlled trial, Physical Therapy 88(4), 674–678.

19.

Lee Minhyeon (2013) Kinematic and kinetic analysis during forward and backward walking, Gait & Posture 38(4), 437–448.

20.

McGie Steven

(2015) Short-term neuroplastic effects of brain-controlled and muscle-controlled electrical stimulation, Neuromodulation 18(3), 233–240.

21.

Myatt,

, Baxter,

, Dougherty,

, Williams,

, Halle,

, Stetts,

, Underwood,

(1995) The cardiopulmonary cost of backward walking at selected speeds, Journal of Orthopaedic and Sports Physical Therapy 21(3), 132–138.

22.

Sabut,

S. K.

(2010) Surface EMG analysis of tibialis anterior muscle in walking with FES in stroke subjects, Annual International Conference of the IEEE Engineering in Medicine and Biololgy, 2010. 5839–5842.

23.

Sabut,

S. K

, Bhattacharya,

S. D

, Manjunatha,

(2013) Functional electrical stimulation on improving foot drop gait in poststroke rehabilitation: a review of its technology and clinical efficacy, Critical Review in Biomedical Engineering 41(2), 149–160.

24.

Sharif Freeha , Ghulam Samina , (2017) Effectiveness of functional electrical stimulation (FES) versus conventional electrical stimulation in gait rehabilitation in patients with stroke, Journal of College of Physicians and Surgeons Pakistan 27(11), 703–706.

25.

Sivaramakrishnan Anjali , Solomon John

, Manikandan Natarajan (2018) Comparison of transcutaneous electrical nerve stimulation (TENS) and functional electrical stimulation (FES) for spasticity in spinal cord injury-a pilot randomized cross-over trial, The Journal of Spinal Cord Medicine 41, 397–406.

26.

Thorstensson,

(1986) How is the normal locomotor program modified to produce backward walking? Experimental Brain Research 61(3), 664–668.

27.

Threlkeld,

A. J

, Horn,

T. S

, Wojtowicz,

, Rooney,

J. G

, Shapiro,

(1989) Kinematics, ground reaction force, and muscle balance produced by backward walking, Journal of Orthopaedic and Sports Physical Therapy 11(2), 56–63.

28.

Tyson,

S. F.

, Ebrahim Sadeghi-Demneh, , Christopher Nester,

(2013) The effects of transcutaneous electrical nerve stimulation on strength, proprioception, balance and mobility in people with stroke: a randomized controlled cross-over trial, Clinical Rehabilitation 27(9), 785–791.

29.

Van Alsenoy Ken , Thomson Athol, , Burnett Angus, , (2019) Reliability and validity of the Zebriz FDM-THQ instrumented treadmill during running trials, Sports Biomechanics 18(5), 501.

30.

Wang Junjie (2018) Effectiveness of backward walking training onspatial-termporal gait characteristics: a. systematic reviewand meta-analysis, Human Movement Science 60, 57–71.

31.

Winter,

D. A.

(1989) Backward walking: a simple reversal of forward walking? Journal of Mot Behavior 21(3), 291–305.

32.

Yang Yea-Ru (2005) Gait outcomes after additional backward walking training in patients with stroke: a randomized controlled trial, Clinical Rehabilitation 19(3), 264–273.