Validity of accelerometry for measurement of activity in people with brain injury

Purpose: To evaluate the validity of a uniaxial accelerometer (MTI Actigraph) for measuring physical activity in people with acquired brain injury (ABI) using portable indirect calorimetry (Cosmed K4b(2)) as a criterion measure. Methods: Fourteen people with ABI and related gait pattern impairment (age 32 +/- 8 yr) wore an MTI Actigraph that measured activity (counts(.)min-(1)) and a Cosmed K4b(2) that measured oxygen consumption (mL(.)kg(-1.)min(-1)) during four activities: quiet sitting (QS) and comfortable paced (CP), brisk paced (BP), and fast paced (FP) walking. MET levels were predicted from Actigraph counts using a published equation and compared with Cosmed measures. Predicted METs for each of the 56 activity bouts (14 participants X 4 bouts) were classified (light, moderate, vigorous, or very vigorous intensity) and compared with Cosmed-based classifications. Results: Repeated-measures ANOVA indicated that walking condition intensities were significantly different (P < 0.05) and the Actigraph detected the differences. Overall correlation between measured and predicted METs was positive, moderate, and significant (r = 0.74). Mean predicted METs were not significantly different from measured for CP and BP, but for FP walking, predicted METs were significantly less than measured (P < 0.05). The Actigraph correctly classified intensity for 76.8% of all activity bouts and 91.5% of light- and moderate-intensity bouts. Conclusions: Actigraph counts provide a valid index of activity across the intensities investigated in this study. For light to moderate activity, Actigraph-based estimates of METs are acceptable for group-level analysis and are a valid means of classifying activity intensity. The Actigraph significantly underestimated higher intensity activity, although, in practice, this limitation will have minimal impact on activity measurement of most community-dwelling people with ABI.

Cardiorespiratory monitoring equipment interferes with whole body impedance measurements

Bioelectrical impedance measurements are widely used for the study of body composition. Commonly measurements are made at 50 kHz to estimate total body water or at low frequencies (< 10 kHz) to estimate extracellular fluid volume. These measurements can be obtained as single measurements at discrete frequencies, or as fitted data interpolated from plots of measurements made at multiple frequencies. This study compared single frequency and multiple frequency (MF) measurements taken in the intensive care environment. MF bioimpedance (4-1000 kHz) was measured on an adult with and without cardiorespiratory monitoring, and on babies in the neonatal intensive care unit. Measurements obtained at individual frequencies were plotted against frequency and examined for the presence of outlying points. Fitted data for measurements obtained at 5 kHz and 50 kHz with and without cardiorespiratory monitoring were compared. Significant artefacts were detected in measurements at approximately 50 kHz and at integral divisions of this frequency as a result of interference from cardiorespiratory monitors. Single frequency measurements taken at these frequencies may be subject to errors that would be difficult to detect without the aid of information obtained from MF measurements.

Pitch jump probability measures for the analysis of snoring sounds in apnea

Obstructive sleep apnea (OSA) is a highly prevalent disease in which upper airways are collapsed during sleep, leading to serious consequences. The gold standard of diagnosis, called polysomnography (PSG), requires a full-night hospital stay connected to over ten channels of measurements requiring physical contact with sensors. PSG is inconvenient, expensive and unsuited for community screening. Snoring is the earliest symptom of OSA, but its potential in clinical diagnosis is not fully recognized yet. Diagnostic systems intent on using snore-related sounds (SRS) face the tough problem of how to define a snore. In this paper, we present a working definition of a snore, and propose algorithms to segment SRS into classes of pure breathing, silence and voiced/unvoiced snores. We propose a novel feature termed the 'intra-snore-pitch-jump' (ISPJ) to diagnose OSA. Working on clinical data, we show that ISPJ delivers OSA detection sensitivities of 86-100% while holding specificity at 50-80%. These numbers indicate that snore sounds and the ISPJ have the potential to be good candidates for a take-home device for OSA screening. Snore sounds have the significant advantage in that they can be conveniently acquired with low-cost non-contact equipment. The segmentation results presented in this paper have been derived using data from eight patients as the training set and another eight patients as the testing set. ISPJ-based OSA detection results have been derived using training data from 16 subjects and testing data from 29 subjects.

Viewpoint-based testing of concurrent components

The use of multiple partial viewpoints is recommended for specification. We believe they also can be useful for devising strategies for testing. In this paper, we use Object-Z to formally specify concurrent Java components from viewpoints based on the separation of application and synchronisation concerns inherent in Java monitors. We then use the Test-Template Framework on the Object-Z viewpoints to devise a strategy for testing the components. When combining the test templates for the different viewpoints we focus on the observable behaviour of the application to systematically derive a practical testing strategy. The Producer-Consumer and Readers-Writers problems are considered as case studies.

The effect of music on monitoring a simulated anaesthetised patient with sonfication

The idea of sonifying anaesthetised patients’ vital signs is gaining acceptance, but some anaesthetists are concerned about additional noise in the operating theatre. We tested the effect of ambient music (jazz, classical and rock) on participants’ ability to monitor a simulated anaesthetised patient with sonification and visual monitors. Participants liked working with ambient music when workload was low. Participants preferred rock music, but reported working better with classical. Ambient music has less effect on participants’ ability to monitor the simulated patient than a distractor task does. We discuss practical implications of these findings.