Most researchers do not approach survey data collection ab initio, but rather draw on "conventional wisdom", often encapsulated in existing textbooks or in what they have been taught at undergraduate or postgraduate level. We thought, therefore, that it would be appropriate to preface our review of empirical studies with a summary of current "expert opinion" and then to seek confirming or refuting evidence from primary research. Sources of expert opinion were key texts on survey methods (e.g. 1,5,13,40 ). These were identified through the personal and institutional libraries of the research team. DatabasesIn our search for primary research studies, previous literature reviews and theoretical articles, we initially prioritised four electronic databases for searching:This review should be reviewed as a guide to best practice, not a definition of best practice. It is a decision aid, not a substitute for critical appraisal of the options available.

This paper presents a new highly accurate gait phase detection system using wearable wireless ultrasonic sensors, which can be used in gait analysis or rehabilitation applications. The gait phase detection system uses the foot displacement information during walking to extract the following gait phases: heel-strike, heel-off, toe-off, and mid-swing. The displacement of foot-mounted ultrasonic sensor is obtained from several passive anchors placed at known locations by employing local spherical positioning technique, which is further enhanced by the combination of recursive Newton-Gauss method and Kalman Filter. The algorithm performance is examined by comparing with a commercial optical motion tracking system with ten healthy subjects and two foot injured subjects. Accurate estimates of gait cycle (with an error of -0.02 ±0.01 s), stance phase(with an error of 0.04±0.03 s), and swing phase (with an error of -0.05±0.03 s) compared to the reference system are obtained. We have also investigated the influence of walking velocities on the performance of the proposed gait phase detection algorithm. Statistical analysis shows that there is no significant difference between both systems during different walking speeds. Moreover, we have tested and discussed the possibility of the proposed system for clinical applications by analyzing the experimental results for both healthy and injured subjects. The experiments show that the estimated gait phases have the potential to become indicators for sports and rehabilitation engineering.

The project has produced a new measure of self-rated pain suitable for use in large-scale population surveys. This instrument assesses not only pain intensity but affective dimensions of pain. It is considered that the validity and reliability testing carried out to date show the measure as acceptable for use in future studies.

In this paper, a low-cost motion analysis system using a wireless ultrasonic sensor network is proposed and investigated. A methodology has been developed to extract spatial-temporal gait parameters including stride length, stride duration, stride velocity, stride cadence, and stride symmetry from 3D foot displacements estimated by the combination of spherical positioning technique and unscented Kalman filter. The performance of this system is validated against a camera-based system in the laboratory with 10 healthy volunteers. Numerical results show the feasibility of the proposed system with average error of 2.7% for all the estimated gait parameters. The influence of walking speed on the measurement accuracy of proposed system is also evaluated. Statistical analysis demonstrates its capability of being used as a gait assessment tool for some medical applications.