No abstract

No abstract

Exoskeleton systems are emerging for robotic assistive surgery and rehabilitation of neurologically impaired patients. A novel upper extremity (UE) exoskeleton has been developed in our lab, potentially to be used for robotic assistive surgery and stroke rehabilitation in our laboratory. The purpose of this study was to introduce the methodology of voluntary control of the UE exoskeleton by processing the range of motion (ROM) of UE joints. Ipsilateral-to-ipsilateral synchronous (IIS) control and ipsilateral-to-contralateral mirror (ICM) control mechanism were designed for UE exoskeleton movement control. A 3D simulation was performed to validate mechanical designs for kinesiologic motion. The performance of the ROM-controlled UE exoskeleton was then validated among six healthy subjects. The UE exoskeleton performed drawing movements in a 2D panel. The drawings created by the UE exoskeleton were compared to the drawings created by a healthy subject to determine the accuracy of the drawing performance. Reliability statistical analysis (Cronbach test) was performed to determine the inter-rater agreement between subject performance and UE exoskeleton performance. Results showed an excellent agreement between the human drawings and exoskeleton drawings (Cronbach Alpha value = 0.904, p<0.01). This study demonstrated that ROM of UE joints can be processed for voluntary control of a UE exoskeleton. Potentially, UE exoskeletons can be used for robotic assistive orthopaedic surgery and UE rehabilitation trainings.

The signals from electromyography (EMG) have been used for volitional control of robotic assistive devices with the challenges of performance improvement. Currently, the most common method of EMG signal processing for robot control is RMS (root mean square)-based algorithm, but system performance accuracy can be affected by noise or artifacts. This study hypothesized that the frequency bandwidths of noise and artifacts are beyond the main EMG signal frequency bandwidth, hence the fixed-bandwidth frequency-domain signal processing methods can filter off the noise and artifacts only by processing the main frequency bandwidth of EMG signals for robot control. The purpose of this study was to develop a cost-effective embedded system and short-time Fourier transform (STFT) method for an EMG-controlled robotic hand. Healthy volunteers were recruited in this study to identify the optimal myoelectric signal frequency bandwidth of muscle contractions. The STFT embedded system was developed using the STM32 microcontroller unit (MCU). The performance of the STFT embedded system was compared with RMS embedded system. The results showed that the optimal myoelectric signal frequency band responding to muscle contractions was between 60 and 80 Hz. The STFT embedded system was more stable than the RMS embedded system in detecting muscle contraction. Onsite calibration was required for RMS embedded system. The average accuracy of the STFT embedded system is 91.55%. This study presents a novel approach for developing a cost-effective and less complex embedded myoelectric signal processing system for robot control.