Digital Biomarkers of Cognitive Frailty: The Value of Detailed Gait Assessment Beyond Gait Speed

Abstract

Background: Cognitive frailty (CF), defined as the simultaneous presence of cognitive impairment and physical frailty, is a clinical symptom in early-stage dementia with promise in assessing the risk of dementia. The purpose of this study was to use wearables to determine the most sensitive digital gait biomarkers to identify CF.

Methods: Of 121 older adults (age = 78.9 ± 8.2 years, body mass index = 26.6 ± 5.5 kg/m2) who were evaluated with a comprehensive neurological exam and the Fried frailty criteria, 41 participants (34%) were identified with CF and 80 participants (66%) were identified without CF. Gait performance of participants was assessed under single task (walking without cognitive distraction) and dual task (walking while counting backward from a random number) using a validated wearable platform. Participants walked at habitual speed over a distance of 10 m. A validated algorithm was used to determine steady-state walking. Gait parameters of interest include steady-state gait speed, stride length, gait cycle time, double support, and gait unsteadiness. In addition, speed and stride length were normalized by height.

Results: Our results suggest that compared to the group without CF, the CF group had deteriorated gait performances in both single-task and dual-task walking (Cohen's effect size d = 0.42-0.97, p < 0.050). The largest effect size was observed in normalized dual-task gait speed (d = 0.97, p < 0.001). The use of dual-task gait speed improved the area under the curve (AUC) to distinguish CF cases to 0.76 from 0.73 observed for the single-task gait speed. Adding both single-task and dual-task gait speeds did not noticeably change AUC. However, when additional gait parameters such as gait unsteadiness, stride length, and double support were included in the model, AUC was improved to 0.87.

Conclusions: This study suggests that gait performances measured by wearable sensors are potential digital biomarkers of CF among older adults. Dual-task gait and other detailed gait metrics provide value for identifying CF above gait speed alone. Future studies need to examine the potential benefits of gait performances for early diagnosis of CF and/or tracking its severity over time.

Keywords: Alzheimer’s disease; Cognitive decline; Cognitive frailty; Cognitive motoric syndrome; Dementia; Digital biomarker; Digital health; Dual-task walking; Gait; Older adults; Wearable.

Figure 1:

Gait was assessed using five wireless wearable sensors attached to the lower back, both the left and right thighs and lower shins. We assessed gait under two walking conditions: 1) Single-task walking: Participants were asked to walk with their habitual gait speed for 10 meters without any distraction 2) Dual-task walking Participants were asked to walk with their habitual gait speed for 10 meters, while loudly counting backward from a two-digit random number

Figure 2:

A) A color-coded illustration of MMSE score (x-axis) and number of frailty phenotype presences (y-axis) with color map based on normalized single-task gait speed. With increase in frailty severity, gait speed is reduced (darker blue color). However, deterioration in cognitive function (lower MMSE) does not necessarily map to slower gait speed under single-task walking. B) A similar color-coded grant as Figure 2A, however with color map based on normalized dual-task gait speed. Unlike to single-task, deterioration in cognitive function led to decrease in normalized dual-task gait speed as well. MMSE: Mini-Mental State Exam; CF: Cognitive-frailty; NCF: Non cognitive-frailty

Figure 3)

Illustration of the receiver operating characteristic (ROC) curve for Model 1 (normalized single-task gait speed), Model 2 (normalized dual-task gait speed), Model 3 (normalized single-task + dual-task gait speed) , and Model 4 (normalized gait speed and gait speed unsteadiness + normalized stride length and stride length unsteadiness + gait cycle time + double support, in both single-task and dual-task walking). While normalized dual-task gait speed improved area under curve (AUC) compared to normalized single-task gait speed, combination of both single-task and dual-task did not noticeably improve AUC. However, addition of other gait metrics during both single-task and dual-task walking (Model 4) noticeably improved AUC.