Posts Tagged dropfoot

[ARTICLE] Speed-adaptive control of functional electrical stimulation for dropfoot correction – Full Text

Abstract

Background

Functional electrical stimulation is an important therapy technique for dropfoot correction. In order to achieve natural control, the parameter setting of FES should be associated with the activation of the tibialis anterior.

Methods

This study recruited nine healthy subjects and investigated the relations of walking speed with the onset timing and duration of tibialis anterior activation. Linear models were built for the walking speed with respect to these two parameters. Based on these models, the speed-adaptive onset timing and duration were applied in FES-assisted walking for nine healthy subjects and ten subjects with dropfoot. The kinematic performance of FES-assisted walking triggered by speed-adaptive stimulation were compared with those triggered by the heel-off event, and no-stimulation walking at different walking speeds.

Results

Higher ankle dorsiflexion angle was observed in heel-off stimulation and speed-adaptive stimulation conditions than that in no-stimulation walking condition at all the speeds. For subjects with stroke, the ankle plantarflexion angle in speed-adaptive stimulation condition was similar to that in no-stimulation walking condition, and it was significant larger than that in heel-off stimulation condition at all speeds.

Conclusions

The improvement in ankle dorsiflexion without worsening ankle plantarflexion in speed-adaptive stimulation condition could be attributed to the appropriate stimulation timing and duration. These results provide evidence that the proposed stimulation system with speed-related parameters is more physiologically appropriate in dropfoot correction, and it may have great potential value in future clinical applications.

 

Background

About three quarters of stroke survivors experience different levels of brain dysfunction and movement disorder [1], which result in lower living quality and limited ability in social activities [2]. Of these subjects, 20% suffer from impaired motor function in the lower extremities. One of such impairments is dropfoot, which is characterized by poor ankle dorsiflexion during the swing phase and an inability to achieve heel strike at the initial contact [34]. Abnormal gaits such as circumduction gait and abnormal foot clearance on the affected side are often found as a method of compensating for excessive hip abduction and pelvis elevation on the unaffected side [5]. This results in gait asymmetry and slow walking speed [6].

Functional electrical stimulation was a representative intervention to correct dropfoot and Liberson et al. first introduced functional electrical stimulation (FES) to correct dropfoot for chronic hemiplegic subjects in the 1960s [7]. An electrical charge is delivered via a pair of electrodes to activate the tibialis anterior (TA), which results in ankle dorsiflexion. Yan et al. applied two dual-channel stimulators to the quadriceps, hamstring, gastrocnemius, and TA to recover motor function of the lower extremities in an early stage after stroke [8]. The stimulation was followed by a predetermined sequence of muscle activations that mimic a healthy gait cycle [9]. The duration of stimulation was five seconds in Yan et al.’s study. However, subjects with different severities of impairment might have different walking speeds [10], which means that a fixed stimulation duration might not be able to account for different walking patterns.

Liberson et al. used the heel-off event detected by a footswitch to trigger the stimulation [7]. However, the reliability of the footswitch controller was significantly reduced when subjects who dragged their feet during walking encountered a slope or an obstacle [11]. Bhadra et al. proposed a manual switch to trigger stimulation as a walking aid for subjects with spinal cord injury (SCI) [12]. However, manual control may distract subjects from maintaining balance and lead to an increased risk of falls [1314]. Furthermore, the cable between the control sensor and stimulator was inconvenient for walking [15].

Instead of a footswitch, Mansfield et al. [16] and Monaghan et al. [17] detected the heel event of the gait cycle in FES-assisted walking using an accelerometer and a uniaxial gyroscope, respectively. The commercially available product WalkAide also uses an accelerometer for this purpose [18]. Electromyography (EMG) signal is also applied as a control source in FES-assisted walking for the detection of volitional intent of muscle [19]. Yeom et al. amplified the EMG signal of the TA and modulated the stimulation intensity in proportion to the integrated EMG envelope. The electrical pulses are then sent to the common peroneal nerve for dropfoot correction [20].

In these studies, FES applied to the TA was mainly triggered by the heel-off event. However, this event occurs during the push-off phase and before TA activation [17]. An earlier start of TA stimulation results in reduced ankle plantarflexion [21]. Spaich et al. suggested implementing a constant time interval before the onset timing of TA stimulation to extend the push-off phase before the ankle dorsiflexion [21]. Some studies have found that walking speed can affect the activation of TA [2223]. Shiavi et al. found that the duration of EMG activity decreased as speed increased [22]. In Winter et al.’s study, the shape of the EMG patterns generally remained similar at the different walking speeds and the duration of EMG activity was closely related to the normalized stride time [23]. Although the duration of TA activation changes with the walking speeds has been reported [24], the selection of speed-adaptive FES parameters for TA has not been investigated.

The objective of this study is to find a more physiologically appropriate FES design for dropfoot correction. Firstly, speed-related changes in onset timing and the duration of TA activation were examined. Next, linear models were built for the walking speed and time interval from the heel-off event to the onset timing of TA activation, as well as for the walking speed and the duration of the TA activation. The speed-adaptive stimulation (SAS) timing and duration were then calculated based on the two models and applied for FES-assisted walking. Finally, the performance of stimulation triggered by SAS, heel-off event (HOS) and no stimulation (NS) were compared during FES-assisted walking on both subjects with stroke and healthy subjects at different walking speeds.[…]

 

Continue —->  Speed-adaptive control of functional electrical stimulation for dropfoot correction | Journal of NeuroEngineering and Rehabilitation | Full Text

 

Fig. 1a The experiment setup of SAS condition; b one healthy subject on the treadmill for system evaluation; c the position of five markers on the right leg

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[ARTICLE] Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction – Full Text

Functional electrical stimulation (FES) is important in gait rehabilitation for patients with dropfoot. Since there are time-varying velocities during FES-assisted walking, it is difficult to achieve a good movement performance during walking. To account for the time-varying walking velocities, seven poststroke subjects were recruited and fuzzy logic control and a linear model were applied in FES-assisted walking to enable intensity- and duration-adaptive stimulation (IDAS) for poststroke subjects with dropfoot. In this study, the performance of IDAS was evaluated using kinematic data, and was compared with the performance under no stimulation (NS), FES-assisted walking triggered by heel-off stimulation (HOS), and speed-adaptive stimulation. A larger maximum ankle dorsiflexion angle in the IDAS condition than those in other conditions was observed. The ankle plantar flexion angle in the IDAS condition was similar to that of normal walking. Improvement in the maximum ankle dorsiflexion and plantar flexion angles in the IDAS condition could be attributed to having the appropriate stimulation intensity and duration. In summary, the intensity- and duration-adaptive controller can attain better movement performance and may have great potential in future clinical applications.

Introduction

Stroke is a leading cause of disability in the lower limb, such as dropfoot (1). A typical cause of dropfoot is muscle weakness, which results in a limited ability to lift the foot voluntarily and an increased risk of falls (24). Great effort is made toward the recovery of walking ability for poststroke patients with dropfoot, such as ankle–foot orthoses (5), physical therapy (6), and rehabilitation robot (7).

Functional electrical stimulation (FES) is a representative intervention to correct dropfoot and to generate foot lift during walking (89). The electrical pulses were implemented via a pair of electrodes to activate the tibialis anterior (TA) muscle and to increase the ankle dorsiflexion angle. The footswitch or manual switch was used to time the FES-assisted hemiplegic walking in previous studies, while they were only based on open-loop architectures. The output parameters of the FES required repeated manual re-setting and could not achieve an adaptive adjustment during walking (1011). Some researchers have found that the maximum ankle dorsiflexion angle by using FES with a certain stimulation intensity had individual differences due to the varying muscle tone and residual voluntary muscle activity and varied during gait cycles (1213). If the stimulation intensity was set to a constant value during the whole gait cycle, the result could be that the muscle fatigues rapidly (14). Another important problem was that the FES using fixed stimulation duration from the heel-off event to the heel-strike event would affect the ankle plantar flexion angle (1516).

Closed-loop control was an effective way to adjust the stimulation parameters automatically, and several control techniques have been proposed (1718). Negård et al. applied a PI controller to regulate the stimulation intensity and obtain the optimal ankle dorsiflexion angle during the swing phase (19). A similar controller was also used in Benedict et al.’s study, and the controller was tested in simulation experiments (20). Cho et al. used a brain–computer interface to detect a patient’s motion imagery in real time and used this information to control the output of the FES (21). Laursen et al. used the electromechanical gait trainer Lokomat combined with FES to correct the foot drop problems for patients, and there were significant improvements in the maximum ankle dorsiflexion angles compared to the pre-training evaluations (22). There were also several studies that used trajectory tracking control to regulate the output and regulate the pulse width and pulse amplitude of the stimulation (23). The module was based on an adaptive fuzzy terminal sliding mode control and fuzzy logic control (FLC) to determine the stimulation output and force the ankle joint to track the reference trajectories. In their study, FES applied to TA was triggered before the heel-off event. Because the TA activation has been proven to occur after the heel-off event and the duration of the TA activation changed with the walking speed (2425), a time interval should be implemented after the heel-off event (26). In Thomas et al.’s study, the ankle angle trajectory of the paretic foot was modulated by an iterative learning control method to achieve the desired foot pitch angles (27). The non-linear relationship between the FES settings and the ankle angle influenced the responses of the ankle motion (28). FLC represents a promising technology to handle the non-linearity and uncertainty without the need for a mathematical model of the plant, which has been widely used in robotic control (29). Ibrahim et al. used FLC to regulate the stimulation intensity of the FES (30), and the same control was used on the regulation of the stimulation duration to obtain a maximum knee extension angle in Watanabe et al.’s study (31). However, most closed-loop controls adjust only one stimulation parameter, and few FES controls considered both varying the stimulation intensity and duration while accounting for the changing walking velocities.

In the present study, an intensity- and duration-adaptive FES was established, the FLC and a linear model were used to regulate the stimulation intensity and duration, respectively. The performance of the intensity- and duration-adaptive stimulation (IDAS) was compared with those of stimulation triggered by no stimulation (NS), heel-off stimulation (HOS), and speed-adaptive stimulation (SAS) for poststroke patients walking on a treadmill. The objective of this study is to find an appropriate FES control strategy to realize a more adaptive ankle joint motion for poststroke subjects.[…]

 

Continue —> Frontiers | Intensity- and Duration-Adaptive Functional Electrical Stimulation Using Fuzzy Logic Control and a Linear Model for Dropfoot Correction | Neurology

Figure 4(A) Ankle angles during the gait cycle for one poststroke subject at free speed; (B) knee angles during the gait cycle for the same poststroke subject at free speed.

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