Research Highlights

Gold (Au) resistive temperature sensors were integrated on flexible polyimide-based neural probes to monitor temperature changes during neural probe implantation and stimulation. Temperature changes were measured as neural probes were implanted to infer the positions of the neural probes, and as the retina or the deep brain region was stimulated electrically.

Muscle activity monitoring or Electromyography (EMG) is a useful tool. However, EMG is typically invasive, expensive and difficult to use for untrained users. A possible solution is textile-based surface EMG (sEMG) integrated into clothing as a wearable device.

Simultaneous acquisition of brain activity signals from the sensorimotor area using NIRS combined with EEG, imagined hand clenching force and speed modulation of brain activity, as well as 6-class classification of these imagined motor parameters by NIRS-EEG were explored. Near infrared probes were aligned with C3 and C4, and EEG electrodes were placed midway between the NIRS probes. NIRS and EEG signals were acquired from 6 healthy subjects during 6 imagined hand clenching force and speed tasks involving the right hand. The results showed that NIRS combined with EEG is effective for simultaneously measuring brain activity of the sensorimotor area.

Distinctive EEG signals from the motor and somatosensory cortex are generated during mental tasks of motor imagery (MI) and somatosensory attentional orientation (SAO). In this study, we hypothesize that a combination of these two signal modalities provides improvements in BCI performance with respect to using the two methods separately, and generate novel types of multi-class BCI systems.

Biomechanical tissue properties have been hypothesized to play a critical role in the quantification of prosthetic socket production for individuals with limb amputation. In this investigation, a novel indenter platform is presented and its performance evaluated for the purposes of residual-limb tissue characterization.

It is important to estimate the 3 degree-of-freedom (DOF) impedance of human forearm and wrist (i.e., forearm prono-supination, and wrist flexion-extension and radial-ulnar deviation) in motor control and in the diagnosis of altered mechanical resistance following stroke. There is, however, a lack of methods to characterize 3 DOF impedance. Thus, we developed a reliable and accurate impedance estimation method, the distal internal model based impedance control (dIMBIC)-based method, to characterize the 3 DOF impedance, including cross-coupled terms between DOFs, for the first time.

Cortical responses to continuous stimuli as recorded using either magneto- or electroencephalography (EEG) have shown power at harmonics of the stimulated frequency, indicating nonlinear behavior. Even though the selection of analysis techniques depends on the linearity of the system under study, the importance of nonlinear contributions to cortical responses has not been formally addressed. The goal of this paper is to quantify the nonlinear contributions to the cortical response obtained from continuous sensory stimulation.

Over the past decade, with the development of machine learning, Discrete Wavelet Transform (DWT) has been widely used in computer-aided epileptic EEG signal analysis as a powerful time-frequency tool. But some important problems have not yet been benefitted from DWT, including epileptic focus localization, a key task in epilepsy diagnosis and treatment. Additionally, the parameters and settings for DWT are chosen empirically or arbitrarily in previous work. In this work, we propose a framework to use DWT and Support Vector Machine (SVM) for epileptic focus localization problem based on EEG.

Providing somatosensory feedback to the user of a myoelectric prosthesis is an important goal since it can improve the utility as well as facilitate the embodiment of the assistive system. Most often, the grasping force was selected as the feedback variable and communicated through one or more individual single channel stimulation units (e.g., electrodes, vibration motors). In the present study, an integrated, compact, multichannel solution comprising an array electrode and a programmable stimulator was presented.

Myoelectric prostheses have many advantages over body-powered prostheses, yet the absence of sensory feedback in myoelectric devices is one reason body-powered devices are often preferred by amputees. While considerable progress has been made in the mechanical design and control of myoelectric prostheses, research on haptic feedback has not had a similar impact. In this study, we seek to develop a fundamental understanding of the utility of force feedback and vision in the functional operation of a body-powered upper-limb prosthesis.