Abstract: Apparatus, systems, and methods for real-time gait modulation are disclosed. In one embodiment, a functional electrical stimulation (FES) device is disclosed comprising one or more wearable articles, a control unit comprising a wireless communication module, one or more processors, one or more memory units, a portable power supply, an electrical muscle stimulation (EMS) generator, and an inertial measurement unit (IMU) comprising at least a gyroscope and an accelerometer. The FES device can also comprise one or more electrode arrays configured to be in physical contact with the limb of the user. The processors can be programmed to execute instructions to retrieve readings from the IMU, calculate a gait cycle percentage by inputting at least the IMU readings into a machine learning algorithm, and instruct the EMS generator to provide electrical stimulation via the one or more electrode arrays based in part on the gait cycle percentage calculated.

Abstract: Apparatus, systems, and methods for real-time gait modulation are disclosed. In one embodiment, a functional electrical stimulation (FES) device is disclosed comprising one or more elastic wearable articles, a control unit comprising a wireless communication module, one or more processors, one or more memory units, a portable power supply, an electrical muscle stimulation (EMS) generator, and an inertial measurement unit (IMU) comprising at least a gyroscope and an accelerometer. The FES device can also comprise one or more electrode arrays configured to be in physical contact with the limb of the user. The processors can be programmed to execute instructions to retrieve readings from the IMU, calculate a gait cycle percentage by inputting at least the IMU readings into a machine learning algorithm, and instruct the EMS generator to provide electrical stimulation via the one or more electrode arrays based in part on the gait cycle percentage calculated.

Abstract: Apparatus, systems, and methods for real-time gait modulation are disclosed. In one embodiment, a functional electrical stimulation (FES) device is disclosed comprising one or more elastic wearable articles, a control unit comprising a wireless communication module, one or more processors, one or more memory units, a portable power supply, an electrical muscle stimulation (EMS) generator, and an inertial measurement unit (IMU) comprising at least a gyroscope and an accelerometer. The FES device can also comprise one or more electrode arrays configured to be in physical contact with the limb of the user. The processors can be programmed to execute instructions to retrieve readings from the IMU, calculate a gait cycle percentage by inputting at least the IMU readings into a machine learning algorithm, and instruct the EMS generator to provide electrical stimulation via the one or more electrode arrays based in part on the gait cycle percentage calculated.