Voluntary participation of hemiplegic patients is crucial for functional electrical stimulation therapy. A wearable functional electrical stimulation system has been proposed for real-time volitional hand motor function control using the electromyography bridge method. Through a series of novel design concepts, including the integration of a detecting circuit and an analog-to-digital converter, a miniaturized functional electrical stimulation circuit technique, a low-power super-regeneration chip for wireless receiving, and two wearable armbands, a prototype system has been established with reduced size, power, and overall cost. Based on wrist joint torque reproduction and classification experiments performed on six healthy subjects, the optimized surface electromyography thresholds and trained logistic regression classifier parameters were statistically chosen to establish wrist and hand motion control with high accuracy. Test results showed that wrist flexion/extension, hand grasp, and finger extension could be reproduced with high accuracy and low latency. This system can build a bridge of information transmission between healthy limbs and paralyzed limbs, effectively improve voluntary participation of hemiplegic patients, and elevate efficiency of rehabilitation training.
Functional electrical stimulation (FES) has been introduced as a neurorehabilitation method to artificially activate sensory and motor systems following central nervous system disease or injury, such as spinal cord injury and stroke (Popović, 2014; Shen et al., 2016; Wade and Gorgey, 2016). The first noninvasive FES system was used for foot drop correction of hemiplegic patients by Liberson et al. (1961). Many novel FES systems have been designed as surface or implantable stimulation systems for controlling arms and hands (Saxena et al., 1995; Ijzerman et al., 1996; Kilgore et al., 1997; Knutson et al., 2012; Hara et al., 2013).
The NESS Handmaster (Ijzerman et al., 1996) and the FES system (Nathan, 1989) belong to the push-button controlled FES method (or switch-based FES). Both of these methods use on/off stimulation with pre-programmed sequences to help spinal cord injury patients recover hand grasp movements and other daily functions. Electromyography (EMG) has been used for on/off control in EMG-triggered FES (Cauraugh et al., 2005) or proportional EMG-controlled FES (Saxena et al., 1995; Thorsen et al., 2001; Hara et al., 2013) and capitalizes on the principle of intension-driven motion. Therapeutic effects were reduced by approximately half if FES was applied without voluntary recipient involvement (Barsi et al., 2008). Preliminary results (McGie et al., 2015) suggest that motor-evoked potential of brain computer interface-controlled FES (Pfurtscheller et al., 2003) and EMG-controlled FES can elicit greater neuroplastic changes than conventional therapy. However, EMG-controlled FES requires some residual movement of the affected arm or hand, so it is not applicable with severely disabled stroke survivors. Contralaterally controlled FES is a promising therapy designed to improve recovery of paretic limbs after stroke. Two case series pilot studies (Knutson et al., 2009, 2014) and an early-phase randomized controlled trial (Knutson et al., 2012) verified the efficiency of contralaterally controlled FES. However, it is important for the success of FES therapy to include the contralateral limb in volitional control of electrically induced contraction in the affected limb.
Based on the success of volitional control of FES, our group previously designed an FES system for restoring motor function in post-stroke hemiplegic patients (Huang et al., 2014). In that system, a frequency-modulation stimulation algorithm based on surface EMG (sEMG) and the support vector machine model were used. However, sEMG thresholds need to be carefully chosen and force reproduction performance has not yet been established. The system is also too difficult to wear and remove.
The specific objectives of this paper were: (1) to use statistical experiments and analyses to optimize the primary parameter “sEMG thresholds” of the frequency-modulation stimulation generation algorithm formerly proposed by our group and to verify the force reproduction performance; (2) to develop a low-complexity algorithm based on logistic regression for hand movement classification achieved by these sEMG thresholds; (3) to develop a wireless and wearable FES system using the EMG-bridge method for real-time volitional hand motor function control, and to assess the feasibility of this system in real-time control of four hand movements. This novel system is a wearable EMG-bridge system that is distributed via a contralateral sEMG-controlled FES system providing more convenience to use at home. The size, power, and overall cost have been significantly reduced compared with the previous prototype (Huang et al., 2014).
Continue —> Real-time and wearable functional electrical stimulation system for volitional hand motor function control using the electromyography bridge method Wang Hp, Bi Zy, Zhou Y, Zhou Yx, Wang Zg, Lv Xy – Neural Regen Res