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Abnormal gait characteristics have been observed in people with diabetic neuropathy, but it is unclear if subtle changes in gait occur in prediabetic people with impaired fasting glucose (IFG). The aims of this study were: (1) to investigate if digital gait measures discriminate people with prediabetes from healthy control participants (HC) and (2) to investigate the relationship between gait measures and clinical scores (concurrent validity). 108 people with prediabetes (71.20 ± 5.11 years) and 63 HC subjects (70.40 ± 6.25 years) wore 6 inertial sensors (Opals by APDM, Clario) while performing the 400-meter fast walk test. Fifty-five measures across 5 domains of gait (Lower Body, Upper Body, Turning, and Variability) were averaged. Analysis of Covariance was used to investigate the group differences, with body mass index as a covariate. Pearson's correlation coefficient assessed the association between the gait measures and the Short Physical Performance Battery (SPPB) score. Nine gait measures were significantly different (p < 10–4) between IFG and HC groups. Step duration, cadence, and turn velocity were the most discriminative measures. In contrast, traditional stop-watch time was not significantly different between groups (p = 0.13), after controlling for BMI. Cadence (r = −0.37, p < 0.001), step duration (r = −0.39, p < 0.001), and turn velocity (r = 0.47, p < 0.001) showed a significant correlation with the SPPB score. Body-worn inertial sensors detected gait impairments in people with prediabetes that related to clinical balance test performance, even when the traditional stop-watch time was not prolonged for the 400-meter walk test. • 108 people with prediabeties and 63 healthy subjects participated in this study. • Objective gait measures from 400-meter walk test were compared between groups. • Step duration, cadence, and turn velocity were the most discriminative measures. • Traditional stop-watch time from 400-meter walk test was not different between groups. • Digital gait measures show a potential to be used in prediabetic clinical trials. [ABSTRACT FROM AUTHOR]

Background: It is unknown whether medication status (off and on levodopa) or laboratory versus home settings plays a role in discriminating fallers and non‐fallers in people with Parkinson's disease (PD). Objectives: To investigate which specific digital gait and turning measures, obtained with body‐worn sensors, best discriminated fallers from non‐fallers with PD in the clinic and during daily life. Methods: We recruited 34 subjects with PD (17 fallers and 17 non‐fallers based on the past 6 month's falls). Subjects wore three inertial sensors attached to both feet and the lumbar region in the laboratory for a 3‐minute walking task (both off and on levodopa) and during daily life activities for a week. We derived 24 digital (18 gait and 6 turn) measures from the 3‐minute walk and from daily life. Results: In clinic, none of the gait and turning measures collected during on levodopa state were significantly different between fallers and non‐fallers. In contrast, digital measures collected in the off levodopa state were significantly different between groups, (average turn velocity, average number of steps to complete a turn, and variability of gait speed, P < 0.03). During daily life, the variability of average turn velocity (P = 0.023) was significantly different in fallers than non‐fallers. Last, the average number of steps to complete a turn was significantly correlated with the patient‐reported outcomes. Conclusions: Digital measures of turning, but not gait, were different in fallers compared to non‐fallers with PD, in the laboratory when off medication and during a daily life. [ABSTRACT FROM AUTHOR]

Background: One difficulty in turning algorithm design for inertial sensors is detecting two discrete turns in the same direction, close in time. A second difficulty is under-estimation of turn angle due to short-duration hesitations by people with neurological disorders. We aimed to validate and determine the generalizability of a: I. Discrete Turn Algorithm for variable and sequential turns close in time and II: Merged Turn Algorithm for a single turn angle in the presence of hesitations. Methods: We validated the Discrete Turn Algorithm with motion capture in healthy controls (HC, n = 10) performing a spectrum of turn angles. Subsequently, the generalizability of the Discrete Turn Algorithm and associated, Merged Turn Algorithm were tested in people with Parkinson's disease (PD, n = 124), spinocerebellar ataxia (SCA, n = 51), and HC (n = 125). Results: The Discrete Turn Algorithm shows improved agreement with optical motion capture and with known turn angles, compared to our previous algorithm by El-Gohary et al. The Merged Turn algorithm that merges consecutive turns in the same direction with short hesitations resulted in turn angle estimates closer to a fixed 180-degree turn angle in the PD, SCA, and HC subjects compared to our previous turn algorithm. Additional metrics were proposed to capture turn hesitations in PD and SCA. Conclusion: The Discrete Turn Algorithm may be particularly useful to characterize turns when the turn angle is unknown, i.e., during free-living conditions. The Merged Turn algorithm is recommended for clinical tasks in which the single-turn angle is known, especially for patients who hesitate while turning. [ABSTRACT FROM AUTHOR]

Although the use of wearable technology to characterize gait disorders in daily life is increasing, there is no consensus on which specific gait bout length should be used to characterize gait. Clinical trialists using daily life gait quality as study outcomes need to understand how gait bout length affects the sensitivity and specificity of measures to discriminate pathological gait as well as the reliability of gait measures across gait bout lengths. We investigated whether Parkinson's disease (PD) affects how gait characteristics change as bout length changes, and how gait bout length affects the reliability and discriminative ability of gait measures to identify gait impairments in people with PD compared to neurotypical Old Adults (OA). We recruited 29 people with PD and 20 neurotypical OA of similar age for this study. Subjects wore 3 inertial sensors, one on each foot and one over the lumbar spine all day, for 7 days. To investigate which gait bout lengths should be included to extract gait measures, we determined the range of gait bout lengths available across all subjects. To investigate if the effect of bout length on each gait measure is similar or not between subjects with PD and OA, we used a growth curve analysis. For reliability and discriminative ability of each gait measure as a function of gait bout length, we used the intraclass correlation coefficient (ICC) and area under the curve (AUC), respectively. Ninety percent of subjects walked with a bout length of less than 53 strides during the week, and the majority (>50%) of gait bouts consisted of less than 12 strides. Although bout length affected all gait measures, the effects depended on the specific measure and sometimes differed for PD versus OA. Specifically, people with PD did not increase/decrease cadence and swing duration with bout length in the same way as OA. ICC and AUC characteristics tended to be larger for shorter than longer gait bouts. Our findings suggest that PD interferes with the scaling of cadence and swing duration with gait bout length. Whereas control subjects gradually increased cadence and decreased swing duration as bout length increased, participants with PD started with higher than normal cadence and shorter than normal stride duration for the smallest bouts, and cadence and stride duration changed little as bout length increased, so differences between PD and OA disappeared for the longer bout lengths. Gait measures extracted from shorter bouts are more common, more reliable, and more discriminative, suggesting that shorter gait bouts should be used to extract potential digital biomarkers for people with PD. [ABSTRACT FROM AUTHOR]