David J. Hewson

Evaluation of driver discomfort during long-duration car driving ☆

The evolution of indices of fatigue, discomfort, and performance of subjects seated for long duration (150 min) in car seats were studied (n=11). Four experimental configurations were used: with and without vibration for two seats (U, uncomfortable; C, comfortable). Surface electromyography (SEMG) data were recorded bilaterally from cervical erector spinae and external oblique muscles. Discomfort increased significantly during the trial, regardless of the experimental condition (p<0.05). Performance was significantly worse for seat U with vibration (p<0.05). The median frequency of SEMG signals did not change between experimental conditions or across time. It would appear that, either the level of discomfort experienced was insufficient to change either performance or SEMG measures, or that the large parameter estimation variance of the SEMG signals might have masked any underlying spectral change. Further refinement of the SEMG signal processing methodology may be necessary to be able to detect fatigue of postural muscles.

Fractal time series analysis of postural stability in elderly and control subjects.

BackgroundThe study of balance using stabilogram analysis is of particular interest in the study of falls. Although simple statistical parameters derived from the stabilogram have been shown to predict risk of falls, such measures offer little insight into the underlying control mechanisms responsible for degradation in balance. In contrast, fractal and non-linear time-series analysis of stabilograms, such as estimations of the Hurst exponent (H), may provide information related to the underlying motor control strategies governing postural stability. In order to be adapted for a home-based follow-up of balance, such methods need to be robust, regardless of the experimental protocol, while producing time-series that are as short as possible. The present study compares two methods of calculating H: Detrended Fluctuation Analysis (DFA) and Stabilogram Diffusion Analysis (SDA) for elderly and control subjects, as well as evaluating the effect of recording duration.MethodsCentre of pressure signals were obtained from 90 young adult subjects and 10 elderly subjects. Data were sampled at 100 Hz for 30 s, including stepping onto and off the force plate. Estimations of H were made using sliding windows of 10, 5, and 2.5 s durations, with windows slid forward in 1-s increments. Multivariate analysis of variance was used to test for the effect of time, age and estimation method on the Hurst exponent, while the intra-class correlation coefficient (ICC) was used as a measure of reliability.ResultsBoth SDA and DFA methods were able to identify differences in postural stability between control and elderly subjects for time series as short as 5 s, with ICC values as high as 0.75 for DFA.ConclusionBoth methods would be well-suited to non-invasive longitudinal assessment of balance. In addition, reliable estimations of H were obtained from time series as short as 5 s.

Evolution in impedance at the electrode-skin interface of two types of surface EMG electrodes during long-term recordings

The evolution in impedance at the electrode-skin interface of Beckman and Red Dot electrodes was assessed during long-term recordings. Impedance was measured between each pair of electrodes, arranged in a bipolar configuration on tibialis anterior (n=13). A waveform constructed of sinusoids of known frequencies, evenly distributed on a log scale from 1-16,384 Hz, was applied through the electrodes, and the result recorded by a DAQ system. SEMG signals were recorded at 1000 Hz during isometric dorsiflexion contractions of 30 s, performed every 15 min for 2 h. Impedance data were acquired at 65,536 Hz immediately before and after SEMG recordings. Large individual differences in impedance levels were observed at low frequencies. At high frequencies, impedance values depended only on the electrode type. Impedance decreased steadily with time for Beckman electrodes (p < 0.05), but did not decrease significantly for Red Dot electrodes. The magnitude of the reduction over time varied widely between individuals, and was related to the initial impedance values. The impedance-bandwidth product remained constant for each electrode type (95% confidence intervals 146.2-148.2 and 126.1-127.8 for Beckman and Red Dot electrodes respectively). When skin impedance is electrically modelled with a simple network containing a resistor and a capacitor, the capacitance varies with the properties of the electrode used, whereas resistance is dependent on the subject. Furthermore, the EMG spectrum is unaffected by impedance provided skin preparation is sufficient to reduce the impedance below 55 komega.

Intrinsic Mode Entropy for Nonlinear Discriminant Analysis

Several methods of measuring entropy of time series have been developed and applied on physiological signals in order to distinguish data sets according to their underlying nonlinear dynamics. These methods are not well adapted for studying the time series in different scales, in the presence of dominant local trends and low-frequency components. In this letter, intrinsic mode entropy (IMEn) is proposed as an entropy measure over multiple oscillation levels. Robustness to local trends is ensured with this new measure, enabling an efficient characterization of the underlying nonlinear dynamics of the time series considered. IMEn is obtained by computing the Sample Entropy (SampEn) of the cumulative sums of the intrinsic mode functions extracted by the empirical mode decomposition method. An example of an application of IMEn is then presented, with the method able to successfully discriminate between two groups of subjects (elderly versus control) for signals of postural stability

Classifying NIR spectra of textile products with kernel methods

This paper describes the use of kernel methods to classify tissue samples using near-infrared spectra in order to discriminate between samples, either with or without elastane. The aim of this real-world study is to identify an alternative method to classify textile products using near-infrared (NIR) spectroscopy in order to improve quality control, and to aid in the detection of counterfeit garments. The principles behind support vector machines (SVMs), of which the main idea is to linearly separate data, are recalled progressively in order to demonstrate that the decision function obtained is a global optimal solution of a quadratic programming problem. Generally, this solution is found after embedding data in another space F with a higher dimension by the means of a specific non-linear function, the kernel. For a selected kernel, one of the most important and difficult subjects concerning SVM is the determination of tuning parameters. Generally, different combinations of these parameters are tested in order to obtain a machine with adequate classification ability. With the kernel alignment method used in this paper, the most appropriate kernel parameters are identified rapidly. Since in many cases, data are embedded in F, a linear principal component (PC) analysis (PCA) can be considered and studied. The main properties and the algorithm of k-PCA are described here. This paper compares the results obtained in prediction for a linear classifier built in the initial space with the PCs from a PCA and those obtained in F with non-linear PCs from a k-PCA. In the present study, even if there are potentially discriminating wavelengths seen on the NIR spectra, linear discriminant analysis and soft independent modelling of class analogy results show that these wavelengths are not sufficient to build a machine with correct generalisation ability. The use of a non-linear method, such as SVM and its corollary methods, kernel alignment and k-PCA, is then justified.

User-centered development and testing of a monitoring system that provides feedback regarding physical functioning to elderly people

Purpose To involve elderly people during the development of a mobile interface of a monitoring system that provides feedback to them regarding changes in physical functioning and to test the system in a pilot study. Methods and participants The iterative user-centered development process consisted of the following phases: (1) selection of user representatives; (2) analysis of users and their context; (3) identification of user requirements; (4) development of the interface; and (5) evaluation of the interface in the lab. Subsequently, the monitoring and feedback system was tested in a pilot study by five patients who were recruited via a geriatric outpatient clinic. Participants used a bathroom scale to monitor weight and balance, and a mobile phone to monitor physical activity on a daily basis for six weeks. Personalized feedback was provided via the interface of the mobile phone. Usability was evaluated on a scale from 1 to 7 using a modified version of the Post-Study System Usability Questionnaire (PSSUQ); higher scores indicated better usability. Interviews were conducted to gain insight into the experiences of the participants with the system. Results The developed interface uses colors, emoticons, and written and/or spoken text messages to provide daily feedback regarding (changes in) weight, balance, and physical activity. The participants rated the usability of the monitoring and feedback system with a mean score of 5.2 (standard deviation 0.90) on the modified PSSUQ. The interviews revealed that most participants liked using the system and appreciated that it signaled changes in their physical functioning. However, usability was negatively influenced by a few technical errors. Conclusion Involvement of elderly users during the development process resulted in an interface with good usability. However, the technical functioning of the monitoring system needs to be optimized before it can be used to support elderly people in their self-management.

Postural time-series analysis using Empirical Mode Decomposition and second-order difference plots

This paper presents a new method for analysis of center of pressure (COP) signals using Empirical Mode Decomposition (EMD). The EMD decomposes a COP signal into a finite set of band-limited signals termed as intrinsic mode functions (IMFs). Thereafter, a signal processing technique used in continuous chaotic modeling is used to investigate the difference between experimental conditions on the summed IMFs. This method is used to detect the degree of variability from a second-order difference plot, which is quantified using a Central Tendency Measure (CTM). Seventeen subjects were tested under eyes open (EO) and eyes closed (EC) conditions, with different vibration frequencies applied for the EC condition in order to provide additional sensory perturbation. This study has demonstrated an effective way to differentiate vibration frequencies by combining EMD and second-order difference (SOD) plots.

Assistive technology design and development for acceptable robotics companions for ageing years

Abstract A new stream of research and development responds to changes in life expectancy across the world. It includes technologies which enhance well-being of individuals, specifically for older people. The ACCOMPANY project focuses on home companion technologies and issues surrounding technology development for assistive purposes. The project responds to some overlooked aspects of technology design, divided into multiple areas such as empathic and social human-robot interaction, robot learning and memory visualisation, and monitoring persons’ activities at home. To bring these aspects together, a dedicated task is identified to ensure technological integration of these multiple approaches on an existing robotic platform, Care-O-Bot®3 in the context of a smart-home environment utilising a multitude of sensor arrays. Formative and summative evaluation cycles are then used to assess the emerging prototype towards identifying acceptable behaviours and roles for the robot, for example role as a butler or a trainer, while also comparing user requirements to achieved progress. In a novel approach, the project considers ethical concerns and by highlighting principles such as autonomy, independence, enablement, safety and privacy, it embarks on providing a discussion medium where user views on these principles and the existing tension between some of these principles, for example tension between privacy and autonomy over safety, can be captured and considered in design cycles and throughout project developments.

Longitudinal evaluation of balance quality using a modified bathroom scale: usability and acceptability

We adapted a commercial bathroom scale in order to acquire the raw data from the weight sensors and then to send them to a server via a mobile phone. We investigated the usability and acceptability of the device in a long-term experiment with 22 elderly users that produced more than 5000 weight recordings. Four basic variables were extracted from the vertical force measurements and the stabilogram. The technology was accepted unreservedly, presumably because it did not differ from devices usually encountered in the home. The quantitative results showed a high variability of day-to-day measurement, which was countered by taking a moving average. A balance index was able to identify changes in balance over time. The preliminary results appear promising.

Univariate and Bivariate Empirical Mode Decomposition for Postural Stability Analysis

The aim of this paper was to compare empirical mode decomposition (EMD) and two new extended methods of EMD named complex empirical mode decomposition (complex-EMD) and bivariate empirical mode decomposition (bivariate-EMD). All methods were used to analyze stabilogram center of pressure (COP) time series. The two new methods are suitable to be applied to complex time series to extract complex intrinsic mode functions (IMFs) before the Hilbert transform is subsequently applied on the IMFs. The trace of the analytic IMF in the complex plane has a circular form, with each IMF having its own rotation frequency. The area of the circle and the average rotation frequency of IMFs represent efficient indicators of the postural stability status of subjects. Experimental results show the effectiveness of these indicators to identify differences in standing posture between groups.