Suchergebnisse

The objectives of this study were (a) to determine errors in wrist angle measurements from a commercially available biaxial electrogoniometer and (b) to develop a calibration routine in order to correct for these errors. Goniometric measurements were collected simultaneously with true angular data using a fixture that allowed wrist movement in one plane while restricting motion in the orthogonal plane. These data were collected in two sets of trials: flexion/extension with radial/ulnar deviation restricted, and radial/ulnar deviation with flexion/extension restricted. During these trials, we studied discrete 30° increments of forearm rotation. The results showed the expected cross talk and zero drift errors during forearm rotation. The application of mathematical equations that describe the effect of goniometer twist resulted in significant error reduction for most forearm rotations. The calibration technique employs both a slope and a displacement transformation to improve the accuracy of angular data. The calibration technique may be used on data collected in the field if forearm rotation is measured simultaneously with the goniometer data.

The goal of this study was to collect anthropometric data that describe the geometry of the surface of the hand and to model this anthropometry as a function of gross external hand measurements. The depth and breadth of each segment of the hand were measured at points that were spaced at approximately equal distances between the joints of the hand. Linear models using hand breadth as the independent variable explained from 12% to 47% of the variation in segment breadths and from 6% to 74% in segment depths. Ellipsoids are used in biomechanical models as an efficient mathematical description of the shape of kinematic segments for use in the determination of contact with other objects. Therefore the primary objectives of this study were to approximate the semiaxis dimensions for these hand segment contact bodies using a linear model of the gross anthropometry and to evaluate the accuracy with which ellipsoids describe the geometry of the hand segments. Graphical comparisons showed that differences between the ellipsoidal approximations and the breadth and depth measurements were largest near the joints. Data collected in this study could be used to create a set of overlapping ellipsoids that would provide a more accurate representation of hand geometry, and this representation could be adapted to biomechanical models that use ellipsoids to define segment geometry.

Objective: The aim of this study was to obtain a comprehensive analysis of the physical workload of clinical staff in long-term care facilities, before and after a safe resident handling program (SRHP). Background: Ergonomic exposures of health care workers include manual handling of patients and many non-neutral postures. A comprehensive assessment requires the integration of loads from these varied exposures into a single metric. Method: The Postures, Activities, Tools, and Handling observational protocol, customized for health care, was used for direct observations of ergonomic exposures in clinical jobs at 12 nursing homes before the SRHP and 3, 12, 24, and 36 months afterward. Average compressive forces on the spine were estimated for observed combinations of body postures and manual handling and then weighted by frequencies of observed time for the combination. These values were summed to obtain a biomechanical index for nursing assistants and nurses across observation periods. Results: The physical workload index (PWI) was much higher for nursing assistants than for nurses and decreased more after 3 years (−24% versus −2.5%). Specifically during resident handling, the PWI for nursing assistants decreased by 41% of baseline value. Conclusion: Spinal loading was higher for nursing assistants than for nurses in long-term care centers. Both job groups experienced reductions in physical loading from the SRHP, especially the nursing assistants and especially while resident handling. Application: The PWI facilitates a comprehensive investigation of physical loading from both manual handling and non-neutral postures. It can be used in any work setting to identify high-risk tasks and determine whether reductions in one exposure are offset by increases in another.