Stephen W. Kelly

Noninvasive beat-to-beat detection of ventricular late potentials

The detection of ventricular late potentials is a subject of some clinical interest. Most techniques currently being investigated rely on signal averaging to extract the microvolt signals from the considerable amounts of noise which are present. Although this approach produces useful results, it does remove any beat-to-beat variations from the signal, and also requires that the signal be present for a considerable number of beats. The paper describes a technique for detecting ventricular late potentials from the body surface, which preserves beat-to-beat variations. The most important aspect of this technique is the use of an adaptive signal enhancer to minimise random noise. Representative results for one normal and two pathological subjects are presented and discussed. A comparison with signal averaging is made and the effectiveness of adaptive signal enhancement is illustrated.

Beat-to-beat detection of His-Purkinje system signals using adaptive filters

Noninvasive techniques to record the activation wave from the His-Purkinje system have so far depended largely on signal averaging. Although this approach produces representative signals, any beat-to-beat variations are removed by the averaging process. These beat-to-beat variations are important in the diagnosis of many heart abnormalities, particularly arrhythmias. The paper describes an experimental system which can detect His-Purkinje system electrograms at the body surface while preserving beat-to-beat variations. The system uses a number of different techniques, but an important feature is the use of an adaptive filter to reduce additive noise. The experimental system is not real-time, as the adaptive filtering is performed offine using software, but a real-time hardware implementation is quite feasible. The systems ability to detect beat-to-beat variations has produced a number of interesting results, which are discussed. These include a cyclic variation in a normal subject, believed to be due to the modulating effects of breathing, and signals from a patient suffering from second degree A-V block.

Electropalatography and the Linguagraph system

This paper describes the technique of electropalatography and the development of Linguagraph, which is a user-friendly, clinical instrument, for measurement of tongue/palate contact, during speech. Linguagraph allows objective assessment of tongue function; appropriate targeting of therapy is therefore possible. Visual feedback is also provided, for therapy, and an objective measurement of outcome is easily obtained. Linguagraph was used, for both therapy and assessment, in a clinical trial. Technical aspects of Linguagraph and of the trial results are presented here. These suggest that the instrument will prove useful in the assessment and management of many speech disorders. Full clinical details of the trial are reported elsewhere.

Weightless Neural System Employing Simple Sensor Data for Efficient Real-Time Round-Corner, Junction and Doorway Detection for Autonomous System Path Planning in Smart Robotic Assisted Healthcare Wheelchairs

Human assistive devices need to be effective with real-time assistance in real world situations: powered wheelchair users require reassuring robust support, especially in the area of collision avoidance. However, it is important that the intelligent system does not take away control from the user. The patient must be allowed to provide the intelligence in the system and the assistive technology must be engineered to be sufficiently smart to recognize and accommodate this. Robotic assistance employed in the healthcare arena must therefore emphasize positive support rather than adopting an intrusive role. Weightless Neural Networks are an excellent pattern recognition tool for real-time applications. This paper introduces a technique for look-ahead identification of open doorways and junctions. Simple sensor data in real-time is used to detect open doors with inherent data uncertainties using a technique applied to a Weightless Neural Network Architecture.

Investigation of Properties of ICmetrics Features

The ICmetrics technology is concerned with identifying acceptable features in an electronic systems operation for encryption purposes. Ideally, the nature of the features should be identical for all of the systems considered, while the values of these features should allow for unique identification of each of the systems. This paper looks at the properties of the Program Counter of a processor core as a potential ICmetrics feature, and explores how the number of its samples being inputted into the ICmetrics system affects stability of the systems performance.

Instrumental assessment and treatment of hypernasality, following maxillofacial surgery, using SNORS : a single case study

The super nasal oral ratiometry system (SNORS) is a commercially available system which measures both nasal and oral airflow during speech, allowing the very rapid movement of the velum to be measured. SNORS uses a modified oxygen mask, which houses the airflow sensors and microphones, and a standard personal computer. By calculating nasalance (the percentage of airflow that is nasal), an estimation of velopharyngeal closure, which is independent of speech intensity, is achieved. SNORS can be used for objective assessment, where the subject is required to speak a number of words selected to demonstrate velopharyngeal function. SNORS also provides biofeedback, using a simple realtime display of nasal and oral airflow. Velopharyngeal insufficiency (VPI) is the inability to make adequate velpharyngeal closure, and may be the result of either neurological or, as in this case, structural abnormalities. It results in abnormal speech characteristics, such as omissions, substitutions or weak articulation of consonants, and hypernasality. T.W., a 52 year old male, had very hypernasal speech following extensive maxillofacial surgery, for the removal of a tonsillar carcinoma. SNORS was successfully used as both an assessment and a therapy tool in the treatment of this patient. The effectiveness of conventional speech and language therapy vs. SNORS biofeedback therapy was compared. Initially, while there was some movement of the velum, the patient could not achieve velopharyngeal closure. Conventional therapy aimed to strengthen and improve the function of the velum and following this there was some minimal improvement: the patient could now achieve, but not maintain, closure. Reassessment, following a non-treatment period, showed little further change. SNORS biofeedback therapy was then given. This raised the patients awareness of his velopharyngeal function, thus helping him to maintain closure, thereby reducing hypernasality. SNORS therapy proved significantly more effective than conventional speech and language therapy, in this case. Further intervention is outlined, and the benefits of multiparameter assessment of speech are discussed.

An instrument for the non-invasive objective assessment of velar function during speech

This paper describes the development of a non-invasive, computer-based, clinical instrument that infers velar function by way of the measurement of nasal and oral airflow. The design criteria of the instrument were based upon a wide ranging review of current practice and available techniques. The instrument measures and displays both nasal and oral airflow, along with the envelope of the speech sound waveform. This allows the clinician to determine whether airflow is associated with oral or nasal airflow and, hence, to infer the position of the velum. Preliminary clinical trials suggest that the instrument provides valuable objective information about the movement of the soft palate, particularly within the time domain. Hence, it is believed that the device provides additional information for the assessment of velar function, complementing those techniques currently employed.

A Study of Factors Affecting Wrist Channel Characteristics for Walking Postures Using Motion Capture

The creation of a 3D animated human model (avatar) to be used in electromagnetic (EM) simulation software is described for low outage body area network application such as healthcare. Scanned surface data of a human model is combined with movement data from a Motion Capture system to simulate an on-body channel between two dual band metallic button antennas (DBMBAs) mounted on the wrist and chest and the wrist and hip during walking. An investigation of how different factors such as human geometry parameters, arm swing and wrist twisting can affect the body-centric channel during walking action is presented together with the relative significance of each of these factors on predicting body-centric channel gain.

RFID tags as passive enabling technology

This paper illustrates the concept of passive tongue touch and tongue proximity wireless sensors. The sensors use the principle of changing the capacitive loading of the tag feed network by moving the tongue closer to the sensor. The application of these devices could be as control actuators for people with severe physical disability.

Real-Time Doorway Detection and Alignment Determination for Improved Trajectory Generation in Assistive Mobile Robotic Wheelchairs

Powered wheelchair users may find operation in enclosed environments such as buildings difficult, a fundamental problem exists: wheelchairs are not much narrower than the doorway they wish to pass through. The ability to detect and pass through doorways represents a major current challenge for automated guided wheelchairs. We utilize a simple doorway pattern recognition technique for fast processing in a real-time system for robotic wheelchair users. We are able to show a 96% detection and identification of 5 individual doorways and an 86% recognition rate of 22 separate approach angles and translations. We conclude that pattern recognition using features obtained from simple constrained infrared ranging sensor data binning can be utilized for fast identification of doorways, and important coarse position and approach angle determination, suitable for real-time trajectory adjustment, representing a significant enhancement in this area.