Evaluation of a Head-Tongue Controller for Power Wheelchair Driving by People With Quadriplegia.

The head-tongue controller (HTC) is a multimodal alternative controller designed for people with quadriplegia to access complex control capabilities by combining tongue and head tracking to offer both discrete and proportional controls in a single controller. In this human study, 17 patients with quadriplegia and current users of alternative controllers were asked to perform four trials of either simple driving tasks or advanced maneuvers in a custom-designed course. Completion time and accuracy were compared between their personal alternative controller (PAC) and various combinations of driving modalities with the HTC. Out of 8 subjects assigned to simple driving, the best HTC trial of 3 subjects was completed faster than their PAC for the tasks of rolling forward and turning around cones, and 5 subjects in rolling backward. Across all these subjects, the average completion time of their best HTC modality is 23 s for rolling forward, 15 s for rolling backward, and 70 s for turning around cones as compared to 19 s, 17 s, and 45 s with their PAC. For advanced driving, the course was completed faster with the HTC by 1 out of 9 subjects, while the best HTC trials of all subjects are less than 1.3 times of their best PAC completion time with an average of 170 s for the HTC and 140 s for their PAC. The qualitative feedback provided by all subjects to a post-study questionnaire scored to an average of 7.5 out of 10 which shows their interests in the HTC and acknowledgement of its usefulness for this population.

A Stand-Alone Intraoral Tongue-Controlled Computer Interface for People With Tetraplegia.

The intraoral Tongue Drive System (iTDS) is an embedded wireless tongue-operated assistive technology developed for people with tetraplegia to provide them a higher level of independence in performing daily living tasks, such as accessing computers, smartphones, and driving wheelchairs. The iTDS was built as an arch-shaped dental retainer hermetically sealed and placed in the buccal shelf area of the mouth, completely hidden from sight. To provide high level of comfort, the iTDS is customized based on the users' oral anatomy to stably fix onto the lower teeth. We have presented a standalone version of the iTDS, capable of recognizing tongue gestures/commands by processing raw magnetic sensor data with a built-in pattern recognition algorithm in real time. The iTDS then sends the commands out in 10-b packets through a custom-designed high-gain intraoral antenna at 2.4 GHz to an external receiver. To evaluate the standalone iTDS performance, four subjects performed a computer access task by issuing random tongue commands over five sessions. Subjects completed 99.2% of the commands, and achieved an information transfer rate of 150.1 b/min. Moreover, a new typing method, designed specifically for the iTDS, resulted in typing at a rate of 3.76 words/min and error rate of 2.23%.

Hardware-efficient robust biometric identification from 0.58 second template and 12 features of limb (Lead I) ECG signal using logistic regression classifier.

The electrocardiogram (ECG), widely known as a cardiac diagnostic signal, has recently been proposed for biometric identification of individuals; however reliability and reproducibility are of research interest. In this paper, we propose a template matching technique with 12 features using logistic regression classifier that achieved high reliability and identification accuracy. Non-invasive ECG signals were captured using our custom-built ambulatory EEG/ECG embedded device (NeuroMonitor). ECG data were collected from healthy subjects (10), between 25-35 years, for 10 seconds per trial. The number of trials from each subject was 10. From each trial, only 0.58 seconds of Lead I ECG data were used as template. Hardware-efficient fiducial point detection technique was implemented for feature extraction. To obtain repeated random sub-sampling validation, data were randomly separated into training and testing sets at a ratio of 80:20. Test data were used to find the classification accuracy. ECG template data with 12 extracted features provided the best performance in terms of accuracy (up to 100%) and processing complexity (computation time of 1.2ms). This work shows that a single limb (Lead I) ECG can robustly identify an individual quickly and reliably with minimal contact and data processing using the proposed algorithm.

Investigation of electrical stimulus on chitosan film based DDS.

Controlled drug release is crucial for targeted implant smart drug delivery system (DDS). In this work a chitosan film loaded with green food coloring is fabricated to demonstrate the concepts of drug release using electrical stimulus. A simulation model is also developed to explain the physical phenomena of this drug release using finite element method (FEM). It is found that drug delivery is increased with applied electric field to the electrodes on chitosan film. The AC electrokinetic force generated from electrical excitation is a factor influencing this phenomenon. Several controlled and stimuli experiments are conducted with different electric fields and frequencies. The spectral absorbance of treated solution after the experiment is measured using a spectrophotometer to quantify the dye release. It is verified statistically with 99% level of significance that the amount of dye release has increased with applied electric field. Thus this work has shown that application of electric field can be a potential candidate for controlled DDS using chitosan film.