Asymmetries Identified in Sit-to-Stand Task Explain Physical Function After Hip Fracture

OpenCap: Human movement dynamics from smartphone videos

Measures of human movement dynamics can predict outcomes like injury risk or musculoskeletal disease progression. However, these measures are rarely quantified in large-scale research studies or clinical practice due to the prohibitive cost, time, and expertise required. Here we present and validate OpenCap, an open-source platform for computing both the kinematics (i.e., motion) and dynamics (i.e., forces) of human movement using videos captured from two or more smartphones. OpenCap leverages pose estimation algorithms to identify body landmarks from videos; deep learning and biomechanical models to estimate three-dimensional kinematics; and physics-based simulations to estimate muscle activations and musculoskeletal dynamics. OpenCap's web application enables users to collect synchronous videos and visualize movement data that is automatically processed in the cloud, thereby eliminating the need for specialized hardware, software, and expertise. We show that OpenCap accurately predicts dynamic measures, like muscle activations, joint loads, and joint moments, which can be used to screen for disease risk, evaluate intervention efficacy, assess between-group movement differences, and inform rehabilitation decisions. Additionally, we demonstrate OpenCap's practical utility through a 100-subject field study, where a clinician using OpenCap estimated musculoskeletal dynamics 25 times faster than a laboratory-based approach at less than 1% of the cost. By democratizing access to human movement analysis, OpenCap can accelerate the incorporation of biomechanical metrics into large-scale research studies, clinical trials, and clinical practice.

Improving Interpretation of the Patient-Reported Outcomes Measurement Information System (PROMIS) Physical Function Scale for Specific Tasks in Community-Dwelling Older Adults

BACKGROUND AND PURPOSE

New generic patient-reported outcomes like the Patient-Reported Outcomes Measurement Information System (PROMIS) are available to physical therapists to assess physical function. However, the interpretation of the PROMIS Physical Function (PF) T-score is abstract because it references the United States average and not specific tasks. The purposes of this study were to (1) determine convergent validity of the PROMIS PF scale with physical performance tests; (2) compare predicted performance test values to normative data; and (3) identify sets of PROMIS PF items similar to performance tests that also scale in increasing difficulty and align with normative data.

METHODS

Community-dwelling older adults (n = 45; age = 77.1 ± 4.6 years) were recruited for this cross-sectional analysis of PROMIS PF and physical performance tests. The modified Physical Performance Test (mPPT), a multicomponent test of mostly timed items, was completed during the same session as the PROMIS PF scale. Regression analysis examined the relationship of mPPT total and component scores (walking velocity, stair ascent, and 5 times sit to stand) with the PROMIS PF scale T-scores. Normative data were compared with regression-predicted mPPT timed performance across PROMIS PF T-scores. The PROMIS PF items most similar to walking, stair ascent, or sit to stand were identified and then PROMIS PF model parameter-calibrated T-scores for these items were compared alongside normative data.

RESULTS AND DISCUSSION

There were statistically significant correlations (r = 0.32-0.64) between PROMIS PF T-score and mPPT total and component scores. Regression-predicted times for walking, stair ascent, and sit-to-stand tasks (based on T-scores) aligned with published normative values for older adults. Selected PF items for stair ascent and walking scaled well to discriminate increasing difficulty; however, sit-to-stand items discriminated only lower levels of functioning.

CONCLUSIONS

The PROMIS PF T-scores showed convergent validity with physical performance and aligned with published normative data. While the findings are not predictive of individual performance, they improve clinical interpretation by estimating a range of expected performance for walking, stair ascent, and sit to stand. These findings support application of T-scores in physical therapy testing, goal setting, and wellness plans of care for community-dwelling older adults.

Beyond Limits: Unmasking Potential Through Movement Discovery

Beth E. Fisher, PT, PhD, FAPTA, is a physical therapist, educator, and scholar whose clinical career has been shaped by numerous observations and experiences of patients' remarkable potential to recover ideal movement capability. Currently, Dr Fisher is a Professor of Clinical Physical Therapy in the Division of Biokinesiology and Physical Therapy at the University of Southern California. She is Director of the Neuroplasticity and Imaging Laboratory, primarily using transcranial magnetic stimulation to investigate brain-behavior relationships during motor skill learning and motor control in both individuals without disabilities and individuals with neurologic disorders. Dr Fisher previously worked at Rancho Los Amigos Medical Center on the Adult Neurology and Brain Injury Services. During her years as a clinician and rehabilitation specialist, it was her greatest ambition to be a part of developing physical therapist interventions that would maximize neural and behavioral recovery in individuals with pathological conditions affecting the nervous system. Toward this goal, she has continued to consult and teach nationally and internationally on current concepts for the treatment of adults with neurological disorders. It has been her consistent clinical observation not only that patients are limited by impairments that result from their injury, but that movement abnormalities are in part the result of a patient's automatic, implicit tendency to "respond" to those impairments via compensation.

A Mechanism-Based Approach to Physical Therapist Management of Pain

Pain reduction is a primary goal of physical therapy for patients who present with acute or persistent pain conditions. The purpose of this review is to describe a mechanism-based approach to physical therapy pain management. It is increasingly clear that patients need to be evaluated for changes in peripheral tissues and nociceptors, neuropathic pain signs and symptoms, reduced central inhibition and enhanced central excitability, psychosocial factors, and alterations of the movement system. In this Perspective, 5 categories of pain mechanisms (nociceptive, central, neuropathic, psychosocial, and movement system) are defined, and principles on how to evaluate signs and symptoms for each mechanism are provided. In addition, the underlying mechanisms targeted by common physical therapist treatments and how they affect each of the 5 categories are described. Several different mechanisms can simultaneously contribute to a patient's pain; alternatively, 1 or 2 primary mechanisms may cause a patient's pain. Further, within a single pain mechanism, there are likely many possible subgroups. For example, reduced central inhibition does not necessarily correlate with enhanced central excitability. To individualize care, common physical therapist interventions, such as education, exercise, manual therapy, and transcutaneous electrical nerve stimulation, can be used to target specific pain mechanisms. Although the evidence elucidating these pain mechanisms will continue to evolve, the approach outlined here provides a conceptual framework for applying new knowledge as advances are made.