Margaret A French's research while affiliated with University of Utah and other places

... In clinical populations such as stroke or osteoarthritis, where differences between the left and right are more apparent, these asymmetry measures may be more valid. This has been the case for 2D video pose estimation systems which demonstrated moderate-to-excellent agreement with gold-standard 3D motion capture for step length asymmetry and step time asymmetry measures in people with stroke (John et al., 2023). Further research should evaluate the validity of these variability and asymmetry parameters with smartphone accelerometry in clinical populations. ...

... From the 26 cross-sectional studies, 14 studies (54%) were considered to be of high quality 67,68,70,76,80,[84][85][86]91,93,94,97,102,103 and 12 studies (46%) of fair quality. 34,71,74,75,82,83,87,89,90,95,98,104 From the 19 cohort studies, nine studies (47%) were considered to be of high quality 13,62-66,79,81,99 and 10 studies (53%) of fair quality. ...

... Reminders were sent to participants to synchronise their devices and complete online assessments, with 65% of participants requiring at least one reminder to achieve a wear time of 77%. 59 This small study included a selective and relatively young population, questioning the feasibility of remote monitoring in older or less healthy individuals. A recent study of 82 people (mean age 80 years) with dementia, including vascular dementia, demonstrated that remote monitoring of physiological parameters was feasible with carer support but needs confirmation. ...

... There is a large current emphasis in neurorehabilitation on outcomes data collection; big data frameworks will undoubtedly lead to very valuable insights for neurorehabilitation [27,28]. When modeling data, key attention to specific outcomes and their context is extraordinarily important. ...

... We think this may have been a result of the HPE algorithm selected. Currently, full-body HPE techniques are typically better at tracking gross body movements, like those in the FTN, compared to smaller motions at extremities like the hand [42]. Our results support this statement as tracking a participant's digits during an HPS task was a challenge for our algorithms. ...

... Furthermore, people with more severe impairment in the acute phase show wider outcome variation in the chronic phase (Prabhakaran et al., 2008). Variation in treatment response even among subpopulations of stroke survivors, as seen in our data, has led to a shift in the field toward precision rehabilitation, which aims to "deliver the right intervention at the right time, to the right individual" (French et al., 2022). However, there are few known 'right interventions' for stroke survivors with chronic, severe sensorimotor impairment. ...

... For example, we did not examine impact of myoelectric control strategies, such as pattern recognition, or surgical interventions, such as targeted muscle innervation, that may improve myoelectric controls and thus impact prosthesis usability experience or prosthesis adoption. Nor did we include factors such as access to prosthetic care, amount and type of prosthetic training, socio-economic status, or psychosocial factors such as presence of depressive symptomology, cognitive abilities, and aspects of the social environment (e.g., marital and employment status), which may impact upper limb use in daily life in prior studies of upper limb impairment [68][69][70]. It is possible these factors and other factors such as prosthesis embodiment may influence Prosthesis Usability and Extent of Prosthesis Adoption as well. ...

... 6,12,13 Explicit learning can be used during gait in both neurologically intact individuals and those post-stroke by providing visual feedback and specific task instructions. [14][15][16] A key feature of this process is that it can be volitionally "switched" on or off in response to context or instructions. 3,13,17,18 Sensorimotor adaptation is an implicit motor learning process that is essential for maintaining well-calibrated movements in response to ever-changing environments and body states. ...

... A computer monitor placed in front of the treadmill provided real-time feedback of participants' left step lengths (The MotionMonitor Toolbox, Innovative Sports Training). We chose to focus on step length because it is a robustly modifiable gait parameter that has frequently been the focus of locomotor learning paradigms (Reisman et al., 2005;Roemmich et al., 2016;French et al., 2018French et al., , 2021Wood et al., 2020Wood et al., , 2021 and because both implicit and explicit forms of motor memory have been observed after learning an altered step length pattern (French et al., 2018(French et al., , 2021Wood et al., 2020Wood et al., , 2021. ...

... For comparison, we recruited a group that performed the same walking pattern using explicit, target error feedback, which does not induce significant exploration. Prior work has demonstrated that use-dependent learning is the predominant source of implicit aftereffects in this target error paradigm (Wood et al., 2020(Wood et al., , 2021, and neither implicit aftereffects nor explicit retention is contaminated by sensory prediction errors. We hypothesized that the reward prediction error group would learn the new walking pattern using greater exploration (a greater increase in motor variability above baseline) and that they would have larger implicit aftereffects and more accurate explicit retention compared with the target error group. ...