Alexander Astaras

Development and User Assessment of a Body-Machine Interface for a Hybrid-Controlled 6-Degree of Freedom Robotic Arm (MERCURY)

This paper presents the development, pilot testing and user assessment results for a body-machine interface (BMI) designed to control a 6-degree of freedom robotic arm, developed by our research team. The BMI was designed to be wearable, immersive and intuitive, constituting the first part of a hybrid real-time user interface. A total of 34 volunteers participated in this study, performing two sets of three tasks in which they controlled the robotic arm, a) within direct line of sight and b) through a video link. All participants completed questionnaires to evaluate their technological background, familiarization with informatics, electronics, robotics and video teleconferencing. At this point of development the system does not capture brainwaves or electric neural input, it simply captures the motion of the operator’s arm. The complete MERCURY prototype system is still under development and additionally comprises a wearable, wireless brain-computer interface (BCI) headset. The BCI headset is currently being integrated into the system and has not yet been pilot tested. The complete hybrid-interface system is primarily intended for research into human-computer interfaces, neurophysiological experiments, as well as industrial applications requiring immersive remote control of robotic machinery.

Pre-clinical physiological data acquisition and testing of the IMAGE sensing device for exercise guidance and real-time monitoring of cardiovascular disease patients

Non-invasive monitoring of a patient’s vital signs outside the medical centre is essential for the remote management of chronic cardiovascular diseases (CVD), such as Heart Failure (HF) and Coronary Artery Disease (CAD). In this work we present preliminary results from pre-clinical testing of the IMAGE sensing platform, a wearable device designed for wireless real-time data acquisition and monitoring of CVD patients’ physiological responses, primarily while they are exercising. The device is capable of acquiring and on-board processing 3-lead electrocardiogram (ECG) and bioimpedance measurements, obtain multi-sensor oxymetry data as well as record torso movement and inclination. Pilot testing has so far primarily focused on optimising the hardware and experimental protocol, using healthy volunteers. A planned clinical study involving CVD patients is expected to commence within the next few months and provide more detailed experimental results, as part of a research and development effort into realtime exercise guidance and early-warning alert generation for patients and clinicians. The IMAGE device has been developed by CSEM SA, a partner in the HeartCycle consortium, a biomedical engineering project co-funded by the EU 7th Framework Programme.

Wireless Brain-Robot Interface: User Perception and Performance Assessment of Spinal Cord Injury Patients

Patients suffering from life-changing disability due to Spinal Cord Injury (SCI) increasingly benefit from assistive robotics technology. The field of brain-computer interfaces (BCIs) has started to develop mature assistive applications for those patients. Nonetheless, noninvasive BCIs still lack accurate control of external devices along several degrees of freedom (DoFs). Unobtrusiveness, portability, and simplicity should not be sacrificed in favor of complex performance and user acceptance should be a key aim among future technological directions. In our study 10 subjects with SCI (one complete) and 10 healthy controls were recruited. In a single session they operated two anthropomorphic 8-DoF robotic arms via wireless commercial BCI, using kinesthetic motor imagery to perform 32 different upper extremity movements. Training skill and BCI control performance were analyzed with regard to demographics, neurological condition, independence, imagery capacity, psychometric evaluation, and user perception. Healthy controls, SCI subgroup with positive neurological outcome, and SCI subgroup with cervical injuries performed better in BCI control. User perception of the robot did not differ between SCI and healthy groups. SCI subgroup with negative outcome rated Anthropomorphism higher. Multi-DoF robotics control is possible by patients through commercial wireless BCI. Multiple sessions and tailored BCI algorithms are needed to improve performance.

Displacement Measurement of a Medical Instrument Inside the Human Body

Several technologies have attempted to measure displacement of objects inside the human body; some of the leading challenges addressed by those technologies are measurement precision, the capacity to operate without clear Line-of-Sight (LOS), susceptibility to electromagnetic interference from other medical instruments, miniaturization, cost effectiveness and safety for both the patient and the medical personnel. The proposed novel method for measuring displacement and tracking the position of a medical instrument inside a human body achieves sub-millimeter accuracy, is characterized by a potentially low cost at high production volumes. It is simple to implement from the biomedical engineering point of view and has been developed to improve the function of medical devices used for invasive or minimally invasive surgery (MIS). This method is based on measuring phase shift displacement at an operating frequency in the gigahertz (GHz) range. The phase shift is detected from the signal emitted by a transmitter, which has been integrated into the medical instrument, with respect to a fixed receiver. It is subsequently translated into a very low frequency voltage, which carries all necessary information concerning transmitter displacement. Simulation results using Verilog-A models and the Spectre simulator provide a mathematical proof of concept model for our novel system design. These results were consequently validated using an experimental setup, which provided millimeter precision results, by the use of commercialy available discrete components and low cost measuring equipment.

Experimental testing of a prototype wireless tele-alerting system for monitoring sleeping infants (smart cot MAIA)

Real time in situ medical monitoring has become increasingly common in the past few decades, driven by the development of a wide variety of affordable sensors and power autonomous, energy efficient microcontroller platforms. Portable and unobtrusive multi-sensor data acquisition is considered routine, including real-time data processing and alerting based on measurements within or around the human body. Project MAIA has developed an intelligent baby cot system capable of monitoring sleeping infants and remotely notifying their carers under pre-programmed circumstances. It aims to add a layer of protection for infants during the first 6 months of their life, primarily targeting medical emergencies such as choking, suffocation and the elusive Sudden Infant Death Syndrome (SIDS). The MAIA system also aims to contribute to current paediatric medical knowledge by providing rare in situ research data.

Development and evaluation of an open source wearable navigation aid for visually impaired users (CYCLOPS)

A wearable computing navigation aid for the visually impaired was designed, tested and evaluated in a series of pilot experiments. The system comprises an ultrasonic transceiver, a digital compass with a built-in accelerometer, sound playback electronics, a vibration motor and a microcontroller, all integrated inside a glove. The system prototype is power autonomous for about an hour and interfaces with the user through both audio and tactile output. The system design goals were reliability, wearability, power autonomy, an intuitive user interface, and open source architecture, low cost and rapid prototyping. A total of 16 pilot testers participated in evaluation experiments, in which they had to use CYCLOPS (http://cyclops-eye.yolasite.com) to navigate an unfamiliar obstacle course towards a goal destination designated by an audio target. 5 of the pilot testers were visually impaired, and 11 were blindfolded seeing individuals. Post-experiment interviews were used to collect qualitative data from all participants. Results indicate that pilot testers of both groups found CYCLOPS to be intuitive to use for blind navigation, even after a brief 5min familiarization period. Several functional corrections and requirements were extracted from the experimental and qualitative data, which will be used to drive the design of future CYCLOPS prototypes.

Commercial BCI Control and Functional Brain Networks in Spinal Cord Injury: A Proof-of-Concept

Spinal Cord Injury (SCI), along with disability, results in changes of brain organization and structure. While sensorimotor networks of patients and healthy individuals share similar patterns, unique functional interactions have been identified in SCI networks. Brain-Computer Interfaces (BCIs) have emerged as a promising technology for movement restoration and rehabilitation of SCI patients. We describe an experimental methodology to combine high-resolution electroencephalography (EEG) for investigation of functional connectivity following SCI and non-invasive BCI control of robotic arms. Two BCI-naïve female subjects, a SCI patient and a healthy control subject participated in the proof-of-concept implementation. They were instructed to perform motor imagery (MI) while watching multiple movements of either arms or legs during walking, while under 128-channel EEG recording. They were, subsequently, asked to control two robotic arms (Mercury v2.0) using a commercial class EEG-BCI. They both achieved comparable performance levels of robotic control, 52.5% for the SCI patient and 56.9% for the healthy control. We performed a feasibility analysis of functional networks on the EEG-BCI recordings. Visual MI allows training on multiple imagined movements and shows promise in investigating differences in functional cortical networks associated with different motor tasks. This approach could allow the implementation of functional network-based BCIs in the future for complex movement control.

A Non-Invasive Medical Decision Support Prototype System for Dermatology Based on Electrical Impedance Spectroscopy (Dermasense)

Premature detection of malignant melanoma remains the primary factor in reducing mortality from this form of cancer. During the last decade diagnostic sensitivity and specificity have improved through the utilization of new computer-based technologies, which help improve lesion selection for pathology review and biopsy. Despite these advances in melanoma diagnosis, initial detection, timely recognition and quick treatment of melanoma remain crucial. Despite the fact that the gold standard for diagnosis remains pathologic examination, this form of cancer has the potential to be diagnosed through non-invasive and radiation-free techniques that are based on electrical impedance spectroscopy (EIS). For this reason, the aim of this study was to design a prototype device (now in its 2nd generation) which will be able to assist clinicians detect early stage melanoma. The DermaSense electrical impedance spectroscopy system (EIS), a novel portable dermatological scanner, offers non-invasive electrical impedance spectroscopy data from multiple dry electrodes placed on a patients skin. A proof of concept prototype of the DermaSense device has been constructed and is currently being evaluated, while clinical pilot measurements related to melanoma are being planned. Initial testing results of the device are promising, enriching the objective physiological evidence available to dermatologists at the point of care. The purpose of this paper is to provide initial results from evaluating the prototype device and to propose statistical processes which can reveal diagnostically meaningful patterns in the data.

Non-intrusive infant monitoring, sensor data fusion and tele-alerting prototype system (asmart cot MAIA2)

Sleep monitoring is an increasingly popular practice, both for medical and lifestyle purposes. In the case of infant safety monitoring, however, most of the devices used are inapplicable due to the utilisation of wires, cords, obtrusive sensors, constant radio wave transmission, low sensitivity and specificity. We proposed and are currently developing the second generation of a portable, unobtrusive infant safety system that can be fitted to most existing cots and can wirelessly tele-alert the infants carers in case of emergency or other pre-defined circumstances. The MAIA system is based on the real-time algorithmic fusion of data obtained from multiple sensors distributed around the infants cot, as part of a reasonably priced system which is quick to install, requires no alteration of existing infant care routines and demonstrates a high level of sensitivity and specificity.