Biomechatronics and Intelligent Robotics Lab

High-Force Fabric Soft Exosuit

This device utilizes precise estimates of the position of the user’s foot through gait cycle detection, whose data is drawn from the IMU, in order to provide adaptive assistance. The controller was placed onto a soft exosuit connected to an origami actuator operated by the folding of conductive material through compression.

The power of the soft exosuit was drawn by a 12V battery that was placed in a pouch at the hip, alongside a buck converter to control the voltage of the system, and a PCB containing the microcontroller, pressure sensor, and solenoid. The design of the controller was inspired by patients diagnosed with drop foot who prioritized portability and ease of access. The controller boasts a design that that utilizes methods of iterative control such as gait cycle detection to determine heel strike, flat foot, midstance, heel off, and toe off in order to properly perform the action needed by the user.



Untethered High Force Hydraulic Artifical Muscle

The usage of hydraulics in biorobotic applications has increased in recent years, due to the advantage of high force to weight ratios, energy and power density. A hydraulically actuated artificial muscle, using the working principle of the pneumatic McKibben muscle, can be used as the actuator for an elbow exoskeletal robot to provide assistance in arm flexion movement, with the advantage of safety and compliance to human biomechanics compared to rigid exoskeletons. The development of the in-house hydraulic driving system and artificial muscle (1” D, 8”/10” L) is documented, with experimentation conducted so far at pressures of up to 140 psi, capable of lifting a weight of up to 82.2 lbs.



Fabric Muscle Activity Sensor

The textile EMG sensor is flexible, foldable, stretchable, washable for multiple times, and easily customizable to meet the heterogeneous needs of SCI individuals. The machine learning algorithms that can estimate the muscle status and the performance of functional ADLs by classification of function ADLs and the detection of muscle spasticity. The soft textronic sensors, its intelligent machine learning algorithms, and biofeedback-based rehabilitation has the potential to enable home-based rehabilitation and encourage more manipulation for function ADLs and independence in SCI and stroke individuals.



Sensing Suit

Wired system: 7 IMUs, IMU receiver, Arduino board and wired insole.
Wireless system: 7 IMUs, IMU receiver, wireless insole and Bluetooth board.