Objective biomarkers of balance and gait for Parkinson's disease using body-worn sensors

Abstract

Balance and gait impairments characterize the progression of Parkinson's disease (PD), predict the risk of falling, and are important contributors to reduced quality of life. Advances in technology of small, body-worn, inertial sensors have made it possible to develop quick, objective measures of balance and gait impairments in the clinic for research trials and clinical practice. Objective balance and gait metrics may eventually provide useful biomarkers for PD. In fact, objective balance and gait measures are already being used as surrogate endpoints for demonstrating clinical efficacy of new treatments, in place of counting falls from diaries, using stop-watch measures of gait speed, or clinical balance rating scales. This review summarizes the types of objective measures available from body-worn sensors. The metrics are organized based on the neural control system for mobility affected by PD: postural stability in stance, postural responses, gait initiation, gait (temporal-spatial lower and upper body coordination and dynamic equilibrium), postural transitions, and freezing of gait. However, the explosion of metrics derived by wearable sensors during prescribed balance and gait tasks, which are abnormal in individuals with PD, do not yet qualify as behavioral biomarkers, because many balance and gait impairments observed in PD are not specific to the disease, nor have they been related to specific pathophysiologic biomarkers. In the future, the most useful balance and gait biomarkers for PD will be those that are sensitive and specific for early PD and are related to the underlying disease process.

Keywords: balance; clinical trials; gait; technology.

Figure 1

Stabilogram from pelvis acceleration traces (lateral versus anteroposterior) during 30s of quiet stance, eyes open, normal stance, from a representative healthy control, untreated patient with early PD, moderate PD patient OFF and ON medication before DBS surgery, and 6 months after bilateral DBS surgery in STN (from left to right). Note that sway area is larger than normal, even in early, untreated PD, and increases with levodopa but decreases with DBS in STN with additive effects of both levodopa and DBS. Stabilograms from center of pressure excursions of a forceplate result in similar metrics of sway in quiet stance (25,27).

Figure 2

Anticipatory postural adjustment (APA) as measured from pelvis lateral acceleration in a representative healthy control and patient with early, untreated PD prior to taking a step. APAs are smaller than normal early in progression of PD, are improved with levodopa but worsened by DBS (8). APAs from center of pressure excursion of a forceplate result in similar APA metrics (39).

Figure 3

A. Receiver Operating Characteristics (ROC) curves for the ITUG parameters (out of 52 parameters measured) that best discriminate between healthy control subjects and untreated PD subjects from Zampieri et al., (10): peak arm velocity of the more affected side (MAS), cadence, peak trunk rotation velocity (yaw), and average turning velocity during 180 degree turn during gait (Adapted from Zampieri et al., JNNP 2010). B. Stride time (extracted from angular velocities of the lower legs) for each stride (consisting of a left plus right step duration) during a 2-minute walk in a representative patient with PD OFF medication and in an age-matched healthy control subject. The coefficient of variation (CoV) is the standard deviation/mean of stride times for the 2-minute walk.

Figure 3

A. Receiver Operating Characteristics (ROC) curves for the ITUG parameters (out of 52 parameters measured) that best discriminate between healthy control subjects and untreated PD subjects from Zampieri et al., (10): peak arm velocity of the more affected side (MAS), cadence, peak trunk rotation velocity (yaw), and average turning velocity during 180 degree turn during gait (Adapted from Zampieri et al., JNNP 2010). B. Stride time (extracted from angular velocities of the lower legs) for each stride (consisting of a left plus right step duration) during a 2-minute walk in a representative patient with PD OFF medication and in an age-matched healthy control subject. The coefficient of variation (CoV) is the standard deviation/mean of stride times for the 2-minute walk.

Figure 4

Power Spectral Densities (PSD) and Frequency Ratios of anteroposterior shank acceleration during a 2-min 360° turn-in-place. The PSD shows that most of the power of leg motion during healthy turning is below 2 Hz, with more high frequencies represented in patients with PD, especially in patients with PD who have freezing of gait (FoG+), The Frequency rations is the power at 3–8Hz/ power at 0.5–3Hz). The higher frequencies represent “trembling in place” and the lower frequencies the stepping movements. From the top to bottom: healthy control subject, a PD subject with freezing of gait OFF medication and a PD subject with similar Motor UPDRS scores, without freezing of gait OFF medication.