TY - JOUR

T1 - The adaptive drop foot stimulator – Multivariable learning control of foot pitch and roll motion in paretic gait

AU - Seel, Thomas

AU - Werner, Cordula

AU - Schauer, Thomas

N1 - Funding Information: This work was conducted within the research project BeMobil, which is supported by the German Federal Ministry of Research and Education (FKZ 16SV7069K).

PY - 2016/11/1

Y1 - 2016/11/1

N2 - Many stroke patients suffer from the drop foot syndrome, which is characterized by a limited ability to lift (the lateral and/or medial edge of) the foot and leads to a pathological gait. In this contribution, we consider the treatment of this syndrome via functional electrical stimulation (FES) of the peroneal nerve during the swing phase of the paretic foot. A novel three-electrodes setup allows us to manipulate the recruitment of m. tibialis anterior and m. fibularis longus via two independent FES channels without violating the zero-net-current requirement of FES. We characterize the domain of admissible stimulation intensities that results from the nonlinearities in patients’ stimulation intensity tolerance. To compensate most of the cross-couplings between the FES intensities and the foot motion, we apply a nonlinear controller output mapping. Gait phase transitions as well as foot pitch and roll angles are assessed in realtime by means of an Inertial Measurement Unit (IMU). A decentralized Iterative Learning Control (ILC) scheme is used to adjust the stimulation to the current needs of the individual patient. We evaluate the effectiveness of this approach in experimental trials with drop foot patients walking on a treadmill and on level ground. Starting from conventional stimulation parameters, the controller automatically determines individual stimulation parameters and thus achieves physiological foot pitch and roll angle trajectories within at most two strides.

AB - Many stroke patients suffer from the drop foot syndrome, which is characterized by a limited ability to lift (the lateral and/or medial edge of) the foot and leads to a pathological gait. In this contribution, we consider the treatment of this syndrome via functional electrical stimulation (FES) of the peroneal nerve during the swing phase of the paretic foot. A novel three-electrodes setup allows us to manipulate the recruitment of m. tibialis anterior and m. fibularis longus via two independent FES channels without violating the zero-net-current requirement of FES. We characterize the domain of admissible stimulation intensities that results from the nonlinearities in patients’ stimulation intensity tolerance. To compensate most of the cross-couplings between the FES intensities and the foot motion, we apply a nonlinear controller output mapping. Gait phase transitions as well as foot pitch and roll angles are assessed in realtime by means of an Inertial Measurement Unit (IMU). A decentralized Iterative Learning Control (ILC) scheme is used to adjust the stimulation to the current needs of the individual patient. We evaluate the effectiveness of this approach in experimental trials with drop foot patients walking on a treadmill and on level ground. Starting from conventional stimulation parameters, the controller automatically determines individual stimulation parameters and thus achieves physiological foot pitch and roll angle trajectories within at most two strides.

KW - Biomedical systems

KW - Drop foot syndrome

KW - Foot motion assessment

KW - Functional electrical stimulation

KW - Gait phase detection

KW - Inertial sensor

KW - Iterative learning control

KW - Multivariable control systems

KW - Neuroprosthetics

KW - Rehabilitation engineering

KW - Validation by experiments

UR - http://www.scopus.com/inward/record.url?scp=84994491696&partnerID=8YFLogxK

U2 - 10.1016/j.medengphy.2016.06.009

DO - 10.1016/j.medengphy.2016.06.009

M3 - Article

C2 - 27396367

AN - SCOPUS:84994491696

VL - 38

SP - 1205

EP - 1213

JO - Medical Engineering and Physics

JF - Medical Engineering and Physics

SN - 1350-4533

IS - 11

ER -