Digital Measures of Postural Sway Quantify Balance Deficits in Spinocerebellar Ataxia

BACKGROUND

Maintaining balance is crucial for independence and quality of life. Loss of balance is a hallmark of spinocerebellar ataxia (SCA).

OBJECTIVE

The aim of this study was to identify which standing balance conditions and digital measures of body sway were most discriminative, reliable, and valid for quantifying balance in SCA.

METHODS

Fifty-three people with SCA (13 SCA1, 13 SCA2, 14 SCA3, and 13 SCA6) and Scale for Assessment and Rating of Ataxia (SARA) scores 9.28 ± 4.36 and 31 healthy controls were recruited. Subjects stood in six test conditions (natural stance, feet together and tandem, each with eyes open [EO] and eyes closed [EC]) with an inertial sensor on their lower back for 30 seconds (×2). We compared test completion rate, test-retest reliability, and areas under the receiver operating characteristic curve (AUC) for seven digital sway measures. Pearson's correlations related sway with the SARA and the Patient-Reported Outcome Measure of Ataxia (PROM ataxia).

RESULTS

Most individuals with SCA (85%-100%) could stand for 30 seconds with natural stance EO or EC, and with feet together EO. The most discriminative digital sway measures (path length, range, area, and root mean square) from the two most reliable and discriminative conditions (natural stance EC and feet together EO) showed intraclass correlation coefficients from 0.70 to 0.91 and AUCs from 0.83 to 0.93. Correlations of sway with SARA were significant (maximum r = 0.65 and 0.73). Correlations with PROM ataxia were mild to moderate (maximum r = 0.56 and 0.34).

CONCLUSION

Inertial sensor measures of extent of postural sway in conditions of natural stance EC and feet together stance EO were discriminative, reliable, and valid for monitoring SCA. © 2024 International Parkinson and Movement Disorder Society.

Gait and turning characteristics from daily life increase ability to predict future falls in people with Parkinson's disease

Objectives

To investigate if digital measures of gait (walking and turning) collected passively over a week of daily activities in people with Parkinson's disease (PD) increases the discriminative ability to predict future falls compared to fall history alone.

Methods

We recruited 34 individuals with PD (17 with history of falls and 17 non-fallers), age: 68 ± 6 years, MDS-UPDRS III ON: 31 ± 9. Participants were classified as fallers (at least one fall) or non-fallers based on self-reported falls in past 6 months. Eighty digital measures of gait were derived from 3 inertial sensors (Opal® V2 System) placed on the feet and lower back for a week of passive gait monitoring. Logistic regression employing a "best subsets selection strategy" was used to find combinations of measures that discriminated future fallers from non-fallers, and the Area Under Curve (AUC). Participants were followed via email every 2 weeks over the year after the study for self-reported falls.

Results

Twenty-five subjects reported falls in the follow-up year. Quantity of gait and turning measures (e.g., number of gait bouts and turns per hour) were similar in future fallers and non-fallers. The AUC to discriminate future fallers from non-fallers using fall history alone was 0.77 (95% CI: [0.50-1.00]). In contrast, the highest AUC for gait and turning digital measures with 4 combinations was 0.94 [0.84-1.00]. From the top 10 models (all AUCs>0.90) via the best subsets strategy, the most consistently selected measures were variability of toe-out angle of the foot (9 out of 10), pitch angle of the foot during mid-swing (8 out of 10), and peak turn velocity (7 out of 10).

Conclusions

These findings highlight the importance of considering precise digital measures, captured via sensors strategically placed on the feet and low back, to quantify several different aspects of gait (walking and turning) during daily life to improve the classification of future fallers in PD.

Biomechanical comparison of frontal plane knee joint moment arms during normal and Tai Chi walking

[Purpose] Medial knee osteoarthritis, a degenerative joint disease, affects adults. The external knee adduction moment, a surrogate knee-loading measure, has clinical implications for knee osteoarthritis patients. Tai Chi is a promising intervention for pain alleviation in knee osteoarthritis; however, the characteristics of external knee adduction moment during Tai Chi have not been established. [Subjects and Methods] During normal and Tai Chi walking, a gait analysis was performed to compare the external knee adduction moment moment-arm characteristics and paired t-tests to compare moment-arm magnitudes. [Results] A significant difference was observed in the average lateral direction of moment-arm magnitude during Tai Chi walking (−0.0239 ± 0.011 m) compared to that during normal walking (−0.0057 ± 0.004 m). No significant difference was found between conditions in average medial direction of moment-arm magnitude (normal walking: 0.0143 ± 0.010 m; Tai Chi walking: 0.0098 ± 0.014 m). [Conclusion] Tai Chi walking produced a larger peak lateral moment-arm value than normal walking during the stance phase, whereas Tai Chi walking and normal walking peak medial moment-arm values were similar, suggesting that medial knee joint loading may be avoided during Tai Chi walking.