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The present study investigated the intrarater reliability, interrater reliability and minimal detectable change at the 90% confidence interval (MDC₉₀) of active shoulder range of motion measurements using digital inclinometry. Two investigators each measured two repetitions of active flexion, abduction, external rotation (ER), and internal rotation (IR) on the nondominant shoulder of 30 asymptomatic participants in a blinded repeated measures design. Results indicated good intrarater reliability with Intraclass Correlation Coefficients (ICCs) (3, k) of Flexion=0.83, Abduction=0.91, ER=0.94 and IR=0.87. Interrater ICC values (2, k) were moderate to good with Flexion=0.58, Abduction=0.95, ER=0.88 and IR=0.93. The MDC₉₀ for the interrater analysis indicated that a change of equal to or greater than 8° (Flexion), 4° (Abduction), 8° (IR), and 9° (ER) would be required to be 90% certain that the change is not due to intertrial variability or measurement error. Digital inclinometry appears to be a reliable instrument for quantifying normal shoulder mobility when strict measurement protocols are adhered to. Clinicians and researchers should consider the MDC values presented when interpreting change values during subsequent measurement sessions.

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Remote monitoring of physical activity using body-worn sensors provides an alternative to assessment of functional independence by subjective, paper-based questionnaires. This study investigated the classification accuracy of a combined surface electromyographic (sEMG) and accelerometer (ACC) sensor system for monitoring activities of daily living in patients with stroke. sEMG and ACC data (eight channels each) were recorded from 10 hemiparetic patients while they carried out a sequence of 11 activities of daily living (identification tasks), and 10 activities used to evaluate misclassification errors (nonidentification tasks). The sEMG and ACC sensor data were analyzed using a multilayered neural network and an adaptive neuro-fuzzy inference system to identify the minimal sensor configuration needed to accurately classify the identification tasks, with a minimal number of misclassifications from the nonidentification tasks. The results demonstrated that the highest sensitivity and specificity for the identification tasks was achieved using a subset of four ACC sensors and adjacent sEMG sensors located on both upper arms, one forearm, and one thigh, respectively. This configuration resulted in a mean sensitivity of 95.0%, and a mean specificity of 99.7% for the identification tasks, and a mean misclassification error of <10% for the nonidentification tasks. The findings support the feasibility of a hybrid sEMG and ACC wearable sensor system for automatic recognition of motor tasks used to assess functional independence in patients with stroke. NIH Public Access

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All subjects who participated in training with the NintendoTM Wii Fit demonstrated statistically significant improvements in gait speed and functional reach after seven weeks of training. Given the potential positive impact that the NintendoTM Wii Fit has on functional reach and gait speed in patients with iSCI, physical therapists may want to incorporate these activities as part of a rehabilitation program.

Shoulder disorders attributed to weight training are well documented in the literature; however, a paucity of evidence-based research exists to describe risk factors inherent to participation. Shoulder joint and muscle characteristics in the recreational weight training (RWT) population were investigated to determine specific risk-related adaptations that may occur from participation. Ninety participants, men between the ages of 19 and 47 (mean age 28.9), including 60 individuals who participated in upper-extremity RWT and 30 controls with no record of RWT participation, were recruited. Active range of motion (AROM), posterior shoulder tightness (PST), body weight-adjusted strength values, and agonist/antagonist strength ratios were compared between the RWT participants and the control group. Statistical analysis identified significant differences (p < 0.001) between the groups when analyzing shoulder mobility. The RWT participants had decreased mobility when compared with the control group for all AROM measurements except external rotation, which was greater. Strength ratios were significantly greater in the RWT group when compared with the control group (p

This study compared the performance of surface electromyographic (sEMG) sensors for different detection conditions affecting the electro-mechanical stability between the sensor and its contact with the skin. These comparisons were made to gain a better understanding of how specific characteristics of sensor design and use may alter the ability of sEMG sensors to detect signals with high fidelity under conditions of vigorous activity. The first part of the study investigated the effect of different detection surface contours and adhesive tapes on the ability of the sensor to remain in electrical contact with the skin. The second part of the study investigated the effects of different skin preparations and hydrophilic gels on the production of movement artifact resulting from sinusoidal and impact mechanical perturbations. Both parts of the study evaluated sensor performance under dry skin and wet skin (from perspiration) conditions. We found that contouring the detection surface and adding a more adhesive double-sided tape were effective in increasing the forces needed to disrupt the electrical contact between the electrodes and the skin for both dry skin and wet skin conditions. The mechanical perturbation tests demonstrated that hydrophilic gel applied to the detection surface of the sensor produced greater movement artifacts compared to sensors without gel, particularly when the sensors were tested under conditions in which perspiration was present on the skin. The use of a surfactant skin preparation did not influence the amount of movement artifacts that resulted from either the sinusoidal or impact perturbations. The importance of these findings is discussed in terms of their implications for improving sEMG signal fidelity through sensor design modifications and procedures for interfacing them with the skin.