Physical Design Factors Contributing to Patient Falls.

OBJECTIVES: The aim of this study was to identify physical design elements that contribute to potential falls in patient rooms. METHODS: An exploratory, physical simulation-based approach was adopted for the study. Twenty-seven subjects, older than 70 years (11 male and 16 female subjects), conducted scripted tasks in a mockup of a patient bathroom and clinician zone. Activities were captured using motion-capture technology and video recording. After biomechanical data processing, video clips associated with potential fall moments were extracted and then examined and coded by a group of registered nurses and health care designers. Exploratory analyses of the coded data were conducted followed by a series of multivariate analyses using regression models. RESULTS: In multivariate models with all personal, environmental, and postural variables, only the postural variables demonstrated statistical significance-turning, grabbing, pushing, and pulling in the bathroom and pushing and pulling in the clinician zone. The physical elements/attributes associated with the offending postures include bathroom configuration, intravenous pole, door, toilet seat height, flush, grab bars, over-bed table, and patient chair. CONCLUSIONS: Postural changes, during interactions with the physical environment, constitute the source of most fall events. Physical design must include simultaneous examination of postural changes in day-to-day activities in patient rooms and bathrooms. Among discussed testable recommendations in the article, the followings design strategies should be considered: (a) designing bathrooms to reduce turning as much as possible and (b) designing to avoid motions that involve 2 or more of the offending postures, such as turning and grabbing or grabbing and pulling, and so on.

Experimental identification of potential falls in older adult hospital patients.

Patient falls within hospitals have been identified as serious but largely preventable incidents, particularly among older adult patients. Previous literature has explored intrinsic factors associated with patient falls, but literature identifying possible extrinsic or situational factors related to falls is lacking. This study seeks to identify patient motions and activities along with associated environmental design factors in a patient bathroom and clinician zone setting that may lead to falls. A motion capture experiment was conducted in a laboratory setting on 27 subjects over the age of seventy using scripted tasks and mockups of the bathroom and clinician zone of a patient room. Data were post-processed using Cortex and Visual3D software. A potential fall was characterized by a set of criteria based on the jerk of the upper body׳s center of mass (COM). Results suggest that only motion-related factors, particularly turning, pushing, pulling, and grabbing, contribute most significantly to potential falls in the patient bathroom, whereas only pushing and pulling contribute significantly in the clinician zone. Future work includes identifying and changing precise environmental design factors associated with these motions for an updated patient room and performing motion capture experiments using the new setup.

Effect of human link length determination on posture reconstruction.

Motion capture experiment results are often used as a means of validation for digital human simulations. Motion capture results are marker positions and joint centers in Cartesian space. However, joint angles are more intuitive and easy to understand compared to marker or joint center positions. Posture reconstruction algorithms are used to map Cartesian space to joint space by re-creating experimental postures with simulation models. This allows for direct comparison between the experimental results and digital human simulations. Besides the inherent experimental errors from motion capture system, one source of simulation error is the determination of the link lengths to be used in the simulation model. The link length errors can propagate through all simulation results. Therefore, it is critical to eliminate the link length errors. The objective of this study is to determine the best method of determining link lengths for the simulation model to best match the model to the experiment results containing errors. Specifically, the way that the link lengths are calculated in the posture reconstruction process from motion capture data has a significant effect on the recreated posture for the simulation model. Three link length calculation methods (experimental-average method, trial-specific method, and T-pose method) are developed and compared to a benchmark method (frame-specific method) for calculating link lengths. The results indicate that using the trial-specific method is the most accurate method when referring to calculating frame-specific link lengths.

Design, control, and sensory feedback of externally powered hand prostheses: a literature review.

In recent years, there has been a steep rise in the quality of prostheses for patients with upper limb amputations. Researchers have begun to identify methods of making prosthetic hands both functional and cosmetically appealing, in contrast to past designs. Many improvements have occurred because of novel design strategies, such as the use of underactuated mechanisms, which allow for more degrees of freedom (DOF) or help reduce the weight of the prosthesis. The increase in functionality is also due in large part to advancements in control strategies for prosthetic hands. One common control method, using electromyographic (EMG) signals generated by muscle contractions, has allowed for an increase in the DOF of hand designs and a larger number of available grip patterns with little added complexity for the wearer. Another recent improvement in prosthetic hand design instead employs electroneurographic (ENG) signals, requiring an interface directly with the peripheral nervous system (PNS) or the central nervous system (CNS). Despite the recent progress in design and control strategies, however, prosthetic hands are still far more limited than the actual human hand. This review outlines the recent progress in the development of electrode-based prosthetic hands, detailing advancements in the areas of design, sensory feedback, and control through EMG and ENG signals (with a particular focus on interfaces with the PNS). The potential benefits and limitations of both control strategies, in terms of signal classification, invasiveness, and sensory feedback, are discussed. Finally, a brief overview of interfaces with the CNS is provided, and potential future developments for prosthetic hand design are discussed.

Physics-based seated posture prediction for pregnant women and validation considering ground and seat pan contacts.

An understanding of human seated posture is important across many fields of scientific research. Certain demographics, such as pregnant women, have special postural limitations that need to be considered. Physics-based posture prediction is a tool in which seated postures can be quickly and thoroughly analyzed, as long the predicted postures are realistic. This paper proposes and validates an optimization formulation to predict seated posture for pregnant women considering ground and seat pan contacts. For the optimization formulation, the design variables are joint angles (posture); the cost function is dependent on joint torques. Constraints include joint limits, joint torque limits, the distances from the end-effectors to target points, and self-collision avoidance constraints. Three different joint torque cost functions have been investigated to account for the special postural characteristics of pregnant women and consider the support reaction forces (SRFs) associated with seated posture. Postures are predicted for three different reaching tasks in common reaching directions using each of the objective function formulations. The predicted postures are validated against experimental postures obtained using motion capture. A linear regression analysis was used to evaluate the validity of the predicted postures and was the criteria for comparison between the different objective functions. A 56 degree of freedom model was used for the posture prediction. Use of the objective function minimizing the maximum normalized joint torque provided an R² value of 0.828, proving superior to either of two alternative functions.