Wearable-Based Stair Climb Power Estimation and Activity Classification

Abstract

Stair climb power (SCP) is a clinical measure of leg muscular function assessed in-clinic via the Stair Climb Power Test (SCPT). This method is subject to human error and cannot provide continuous remote monitoring. Continuous monitoring using wearable sensors may provide a more comprehensive assessment of lower-limb muscular function. In this work, we propose an algorithm to classify stair climbing periods and estimate SCP from a lower-back worn accelerometer, which strongly agrees with the clinical standard (r = 0.92, p < 0.001; ICC = 0.90, [0.82, 0.94]). Data were collected in-lab from healthy adults (n = 65) performing the four-step SCPT and a walking assessment while instrumented (accelerometer + gyroscope), which allowed us to investigate tradeoffs between sensor modalities. Using two classifiers, we were able to identify periods of stair ascent with >89% accuracy [sensitivity = >0.89, specificity = >0.90] using two ensemble machine learning algorithms, trained on accelerometer signal features. Minimal changes in model performances were observed using the gyroscope alone (±0–6% accuracy) versus the accelerometer model. While we observed a slight increase in accuracy when combining gyroscope and accelerometer (about +3–6% accuracy), this is tolerable to preserve battery life in the at-home environment. This work is impactful as it shows potential for an accelerometer-based at-home assessment of SCP.

Minimal power required to ascend a flight of stairs versus actual power measured with body‐fixed sensors in adults aged 19–85 years

“…However, the applicability of these methodologies in clinical settings is limited due to practical reasons (e.g., high cost, the need of trained personnel, low transferability) 8 . Considering their accessibility and rapid advancements, wearable sensors and smartphones offer a promising avenue to measure power production during functional activities, such as chair rising 9–12 and stair‐climbing (SC) 9,13,14 . While monitoring of sit‐to‐stand performance is receiving most attention, SC is one of the elementary movements to maintain independence in public and home environments 15,16 and therefore a crucial activity to monitor in older adults.…”

“…8 Considering their accessibility and rapid advancements, wearable sensors and smartphones offer a promising avenue to measure power production during functional activities, such as chair rising [9][10][11][12] and stair-climbing (SC). 9,13,14 While monitoring of sit-to-stand performance is receiving most attention, SC is one of the elementary movements to maintain independence in public and home environments 15,16 and therefore a crucial activity to monitor in older adults. Previous research demonstrated that SC power can be estimated using a single lumbar-worn sensor, 9 and that it is highly related to a "gold standard" methodology for measuring lower-limb muscle power (i.e., an isokinetic dynamometer).…”

Older adults’ lower-limb muscle power production throughout a full flight of stairs: Reliability and comparison between different stair models

“…Kinematic data can be collected by means of body-fixed sensors, providing data on power production during every step of a stair [ 15 , 20 ]. We have previously demonstrated that sensor-based SC power is highly related (r = 0.80) to leg-extensor power in a group of young, middle-aged and older adults [ 15 ].…”