Horizon scanning is becoming particularly important in the medical industry, in the identification and evaluation of emerging technologies. This paper examines the role biomedical engineers may have in horizon scanning new medical technologies and considers whether this is a useful activity for biomedical engineers. A horizon scanning methodology for conducting studies of emerging medical technologies is introduced, consisting of the three main phases of (a) a systematic literature review, in which a set approach is taken to the gathering of information; (b) scanning for publications across a range of different sources; and (c) consideration of the literature in relation to fixed benchmarks to indicate the quality of published information and reported achievements. This methodology has been successfully applied by the authors in a horizon scanning study for the purpose of advising a Government agency on the status of remote patient monitoring technology.

BackgroundChanges in nonlinear neuronal mechanisms of EEG generation in the course of general anaesthesia have been extensively investigated in research literature. A number of EEG signal properties capable of tracking these changes have been reported and employed in anaesthetic depth monitors. The degree of phase coupling between different spectral components is a marker of nonlinear EEG generators and is claimed to be an important aspect of BIS. While bicoherence is the most direct measure of phase coupling, according to published research it is not directly used in the calculation of BIS, and only limited studies of its association with anaesthetic depth and level of consciousness have been published. This paper investigates bicoherence parameters across equal band and unequal band bifrequency regions, during different states of anaesthetic depth relating to routine clinical anaesthesia, as determined by visual inspection of EEG.Methods41 subjects scheduled for day surgery under general anaesthesia were recruited into this study. EEG bicoherence was analysed using average and smoothed-peak estimates calculated over different regions on the bifrequency plane. Statistical analysis of associations between anaesthetic depth/state of consciousness and bicoherence estimates included linear regression using generalised linear mixed effects models (GLMs), ROC curves and prediction probability (Pk).ResultsBicoherence estimates for the δ_θ region on the bifrequency plane were more sensitive to anaesthetic depth changes compared to other bifrequency regions. Smoothed-peak bicoherence displayed stronger associations than average bicoherence. Excluding burst suppression and large transients, the δ_θ peak bicoherence was significantly associated with level of anaesthetic depth (z = 25.74, p < 0.001 and R2 = 0.191). Estimates of Pk for this parameter were 0.889(0.867-0.911) and 0.709(0.689-0.729) respectively for conscious states and anaesthetic depth levels (comparable BIS estimates were 0.928(0.905-0.950) and 0.801(0.786-0.816)). Estimates of linear regression and areas under ROC curves supported Pk findings. Bicoherence for eye movement artifacts were the most distinctive with respect to other EEG patterns (average |z| value 13.233).ConclusionsThis study quantified associations between deepening anaesthesia and increase in bicoherence for different frequency components and bicoherence estimates. Increase in bicoherence was also established for eye movement artifacts. While identified associations extend earlier findings of bicoherence changes with increases in anaesthetic drug concentration, results indicate that the unequal band bifrequency region, δ_θ, provides better predictive capabilities than equal band bifrequency regions.

This paper describes a method of detecting and analyzing breathing rate and approximate depth during physical activity in a Bluetooth Wireless On-Body-Network (OBN) in the context of a Spinal Cord Injured patient. Conventional signal processing techniques and sensor fusion through a Linear Kalman Filter will be used to fuse signals from a piezoelectric breathing band and two tri-axis accelerometers. Results will show that the proposed method provides very accurate measurements of breathing rate and depth at rest and during physical activity.

Pedometers are known to have steps estimation issues. This is mainly attributed to their innate acceleration based measuring sensory. A micro-machined gyroscope (better immunity to acceleration) based pedometer is proposed. Through syntactic data recognition of apriori knowledge of human shank's dynamics and temporally précised detection of heel strikes permitted by Wavelet decomposition, an accurate and robust pedometer is acquired.

Monitoring a range of physiological parameters in SCI patients during extended periods of daily activity and during therapy in rehabilitation raises a no of practical issues. A totally portable system with sensors and data logger can provide a clinically useful monitoring system for SCI to study the behaviour of physiological parameters during rehabilitation allows it to be prescribed and optimised to match the individual patient's needs. Issues affecting our study will be illustrated by looking at results in the most compromised tetraplegic group.