Stride variability measures derived from wrist- and hip-worn accelerometers

Abstract

Many epidemiological and clinical studies use accelerometry to objectively measure physical activity using the activity counts, vector magnitude, or number of steps. These measures use just a fraction of the information in the raw accelerometry data as they are typically summarized at the minute level. To address this problem, we define and estimate two measures of temporal stride-to-stride gait variability based on raw accelerometry data: Amplitude Deviation (AD) and Phase Deviation (PD). We explore the sensitivity of our approach to on-body placement of the accelerometer by comparing hip, left and right wrist placements. We illustrate the approach by estimating AD and PD in 46 elderly participants in the Developmental Epidemiologic Cohort Study (DECOS) who worn accelerometers during a 400 meter walk test. We also show that AD and PD have a statistically significant association with the gait speed and sit-to-stand test performance.

An Automatic Gait Feature Extraction Method for Identifying Gait Asymmetry Using Wearable Sensors

“…However there is no recommended systematic procedure for developing a GA assessment. General measurement of gait variability includes cadence, stride length and gait velocity [ 70 ], alone or in combination with other outcome measures such as stride to stride variability assessed by an accelerometer, gyroscope and magnetometer [ 24 , 36 , 39 , 40 ]. Researchers presented a set of 31 gait variables in [ 71 ] and 16 variables were investigated.…”

“…A variety of wearable sensors including accelerometer, gyroscope, magnetometer, foot pressure sensor, inclinometer, and goniometer [ 23 , 24 ] are generally used to measure various characteristics of human gait. Inertial Measurement Unit (IMU) sensors are used in different situations such as monitoring of post-operative gait abnormalities [ 25 ], stride variability [ 24 ], measurement of GA [ 26 ], fall-related gait characteristics measured on a treadmill in daily life [ 27 ], nature of the Parkinsonian gait [ 28 ] and human waking foot trajectory [ 29 ].…”

“…A variety of wearable sensors including accelerometer, gyroscope, magnetometer, foot pressure sensor, inclinometer, and goniometer [ 23 , 24 ] are generally used to measure various characteristics of human gait. Inertial Measurement Unit (IMU) sensors are used in different situations such as monitoring of post-operative gait abnormalities [ 25 ], stride variability [ 24 ], measurement of GA [ 26 ], fall-related gait characteristics measured on a treadmill in daily life [ 27 ], nature of the Parkinsonian gait [ 28 ] and human waking foot trajectory [ 29 ]. Accelerometer based gait parameters such as times of stance, swing, single support and double [ 30 ]; stride and stance phase [ 31 ]; gait velocity, cadence and step length [ 32 ]; step number, moving distances, every step instant speed and average speed [ 33 ]; step counting [ 34 , 35 ]; times of heel strike, toe strike, heel-off, and toe-off [ 36 ]; stride length and duration [ 37 ]; walking distance, time and speed [ 38 ] were investigated.…”

“…Although, IMU based gait analysis methods are available, specific GA was actually found in few studies [ 30 ]. Some studied a single gait parameter [ 24 ], single sensor [ 12 ] or applied simple statistical methods for comparisons [ 38 ]. Force-sensitive resistors placed in insoles to detect ground contact were used to estimate the stance time for GA [ 39 ].…”

Expanding the Toolkit for Studies of Aging

“…Metrics of behavioral variability, particularly with regard to higher level functions, may provide more sensitive indicators of adaptability and health (6). Leveraging the diverse facets of behaviors which can be recorded via prolonged behavioral recordings will allow investigators to examine metrics of behavioral capacity versus function in real world settings and provide the opportunity for more nuanced and targeted interventions.…”