The sensitivity of three commonly used outcome measures to detect change amongst patients receiving inpatient rehabilitation following stroke.

OBJECTIVE: To investigate the sensitivity of three commonly used functional outcome measures to detect change over time in subjects receiving inpatient rehabilitation post stroke. DESIGN: Subjects were assessed within one week of admission and one week of discharge from an inpatient rehabilitation facility. Several parameters of sensitivity were calculated, including floor and ceiling effects, the percentage of subjects showing no change and the effect size of the change between admission and discharge. SETTING: The medical rehabilitation ward of an inpatient rehabilitation facility. SUBJECTS: Seventy-eight subjects receiving inpatient rehabilitation following a first or recurrent stroke. MEASURES: Five-metre walk, comfortable pace (gait speed), the Berg Balance Scale and the Motor Assessment Scale. RESULTS: Sixty-one subjects had complete admission and discharge data. Gait speed and the Berg Balance Scale were both sensitive to change and demonstrated large effect sizes. The Motor Assessment Scale item five also showed a large effect size and was able to detect change amongst lower functioning subjects. The other items of the Motor Assessment Scale were less useful, in particular, the effect sizes for upper extremity change scores were small (d=0.36-0.5) and the majority of subjects (44.3-63.9%) showed no change over time on these measures. CONCLUSION: Gait speed, the Berg Balance Scale and the Motor Assessment Scale item five were sensitive to change over time in this sample.

Compensation of limb weight on interfaced raw torque signals from a KIN-COM dynamometer to an AMLAB workstation.

The effect of gravity should be considered when using isokinetic devices to measure human movement performance. In most isokinetic dynamometers gravity compensation is controlled by software through a gravity correction option. However in some complex research protocols the dynamometer signal acquisition and processing capability is not adequate to effectively synchronize or process a wide range of captured signals. Therefore when the force/torque signals from a commonly used dynamometer such as KIN-COM are interfaced into a signal processing workstation such as AMLAB, it is necessary to further process the received raw signals for gravity correction. The aim of this study was to evaluate the effectiveness of an AMLAB-based instrument designed for gravity compensation of raw torque signals acquired from a KIN-COM dynamometer. To check the accuracy of weight compensation within the AMLAB, environment, torque signals produced by a known weight during a 180-degree range of KIN-COM lever arm movement were compared with and without weight compensation. The results indicated that this technique is an accurate means for weight compensation when raw torque signals from a KIN-COM dynamometer are interfaced to an AMLAB workstation.

An integrated AMLAB-based system for acquisition, processing and analysis of evoked EMG and mechanical responses of upper limb muscles.

An integrated multi-channel AMLAB-based data acquisition, processing and analysis system has been developed to simultaneously display, quantify and correlate electromyographic (EMG) activity, resistive torque, range of motion, and pain responses evoked by passive elbow extension in humans. The system was designed around the AMLAB analog modules and software objects called ICAMs. Each channel consisted of a time and frequency domain block, a torque and angle measurement block, an experiment number counter block and a data storage and retrieval block. The captured data in each channel was used to display and quantify: raw EMG, rectified EMG, smoothed rectified EMG, root-mean-squared EMG, fast Fourier transformed (FFT) EMG, and normalized power spectrum density (NPSD) of EMG. Torque and angle signals representing elbow extension measured by a KIN-COM dynamometer during neural tension testing, as well as signals from an electronic pain threshold marker were interfaced to AMLAB and presented in one integrated display. Although this system has been designed to specifically study the patterns and nature of evoked motor responses during clinical investigation of carpal tunnel syndrome (CTS) patients, it could equally well be modified to allow acquisition, processing and analysis of EMG signals in other studies and applications. In this paper, we present for the first time the steps involved in the design, implementation and testing of an integrated AMLAB-based system to study and analyse the mechanically evoked electromyographic, torque and ROM signals and correlate various levels of pain to these signals. We also present samples of resistive torque ROM, and raw and processed EMG recordings during passive elbow extension.