A microcontroller platform for the rapid prototyping of functional electrical stimulation-based gait neuroprostheses.

Functional electrical stimulation (FES) has been used over the last decades as a method to rehabilitate lost motor functions of individuals with spinal cord injury, multiple sclerosis, and post-stroke hemiparesis. Within this field, researchers in need of developing FES-based control solutions for specific disabilities often have to choose between either the acquisition and integration of high-performance industry-level systems, which are rather expensive and hardly portable, or develop custom-made portable solutions, which despite their lower cost, usually require expert-level electronic skills. Here, a flexible low-cost microcontroller-based platform for rapid prototyping of FES neuroprostheses is presented, designed for reduced execution complexity, development time, and production cost. For this reason, the Arduino open-source microcontroller platform was used, together with off-the-shelf components whenever possible. The developed system enables the rapid deployment of portable FES-based gait neuroprostheses, being flexible enough to allow simple open-loop strategies but also more complex closed-loop solutions. The system is based on a modular architecture that allows the development of optimized solutions depending on the desired FES applications, even though the design and testing of the platform were focused toward drop foot correction. The flexibility of the system was demonstrated using two algorithms targeting drop foot condition within different experimental setups. Successful bench testing of the device in healthy subjects demonstrated these neuroprosthesis platform capabilities to correct drop foot.

[1]  T. A. Thrasher,et al.  Neuroprosthesis for Retraining Reaching and Grasping Functions in Severe Hemiplegic Patients , 2005, Neuromodulation : journal of the International Neuromodulation Society.

[2]  Vassilis C. Moulianitis,et al.  A closed-loop drop-foot correction system with gait event detection from the contralateral lower limb using fuzzy logic , 2011, 2011 10th International Workshop on Biomedical Engineering.

[3]  Erwin Schoonderwaldt,et al.  MusicJacket—Combining Motion Capture and Vibrotactile Feedback to Teach Violin Bowing , 2011, IEEE Transactions on Instrumentation and Measurement.

[4]  J. Higginson,et al.  Combined effects of fast treadmill walking and functional electrical stimulation on post-stroke gait. , 2011, Gait & posture.

[5]  R. Stein,et al.  Surface Electrical Stimulation for Foot Drop: Control Aspects and Walking Performance , 2008 .

[6]  J. Norton,et al.  Clinical use of the Odstock dropped foot stimulator: its effect on the speed and effort of walking. , 1999, Archives of physical medicine and rehabilitation.

[7]  Young-Hui Chang,et al.  Autogenic EMG-controlled functional electrical stimulation for ankle dorsiflexion control , 2010, Journal of Neuroscience Methods.

[8]  Derek T O'Keeffe,et al.  Stimulus artifact removal using a software-based two-stage peak detection algorithm , 2001, Journal of Neuroscience Methods.

[9]  M Mahadevappa,et al.  Design of a programmable multi-pattern FES system for restoring foot drop in stroke rehabilitation , 2010, Journal of medical engineering & technology.

[10]  G M Lyons,et al.  A system for the delivery of programmable, adaptive stimulation intensity envelopes for drop foot correction applications. , 2006, Medical engineering & physics.

[11]  Matthew B. Bouchard,et al.  SPLASSH: Open source software for camera-based high-speed, multispectral in-vivo optical image acquisition , 2010, Biomedical optics express.

[12]  James B. Fallon,et al.  A novel stimulus artifact removal technique for high-rate electrical stimulation , 2008, Journal of Neuroscience Methods.

[13]  P. Taylor,et al.  CORRECTION OF BI-LATERAL DROPPED FOOT USING THE ODSTOCK 2 CHANNEL STIMULATOR (O2CHS) , 1999 .

[14]  B.T. Smith,et al.  Evaluation of force-sensing resistors for gait event detection to trigger electrical stimulation to improve walking in the child with cerebral palsy , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[15]  Patrick E. Crago,et al.  Stimulus artifact removal in EMG from muscles adjacent to stimulated muscles , 1996, Journal of Neuroscience Methods.

[16]  Michael Eisenberg,et al.  The LilyPad Arduino: Toward Wearable Engineering for Everyone , 2008, IEEE Pervasive Computing.

[17]  J. Higginson,et al.  Functional Electrical Stimulation of Ankle Plantarflexor and Dorsiflexor Muscles: Effects on Poststroke Gait , 2009, Stroke.

[18]  T. Sinkjaer,et al.  A review of portable FES-based neural orthoses for the correction of drop foot , 2002, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[19]  Richard A. Brand,et al.  The biomechanics and motor control of human gait: Normal, elderly, and pathological , 1992 .

[20]  Closed-Loop Control for FES : Past Work and Future Directions Lynch CL , 2010 .

[21]  J. Norton,et al.  Patients' perceptions of the Odstock Dropped Foot Stimulator (ODFS) , 1999, Clinical rehabilitation.

[22]  R. Conway,et al.  A Programmable and Portable NMES Device for Drop Foot Correction and Blood Flow Assist Applications , 2009, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[23]  C. Lynch,et al.  Functional Electrical Stimulation , 2017, IEEE Control Systems.

[24]  Sarah Westcott McCoy,et al.  Functional electrical stimulation to dorsiflexors and plantar flexors during gait to improve walking in adults with chronic hemiplegia. , 2010, Archives of physical medicine and rehabilitation.

[25]  Jin-Shin Lai,et al.  Development of the FES system with neural network + PID controller for the stroke , 2005, 2005 IEEE International Symposium on Circuits and Systems.

[26]  Milos R. Popovic,et al.  Functional Electrical Stimulation. , 2006, Artificial organs.