Using Smartphone Inertial Measurement Unit for Analysis of Human Gait

Abstract

The study was aimed at searching the characteristic features of a human gait during a conventionally used neurologic walking test with the help of sensors (3D accelerometer and gyroscope) in a smartphone mounted on the person's head. This allowed reducing the amount of analyzed data and saving time for analysis in comparison with motion video capture methods. It has been found that merely one inertial unit is good enough to detect the gait left-right asymmetry in healthy subjects. Several parameters were derived, one of them (acceleration shock) proved to be the most informative one. The gyroscope signal allowed detecting the characteristics of the gait in Parkinson's disease patients seen as the excess of the power spectrum density in all three axes. Therefore, this study was aimed to extract amplitude and spectral parameters from acceleration and rotation rate signals of smartphone-based IMU attached to the head during the long version of the TUG test in a group of neurologically healthy young subjects.

Gait Characteristics Analyzed with Smartphone IMU Sensors in Subjects with Parkinsonism under the Conditions of “Dry” Immersion

“…It was noted that the sensor offsets were probably pre-calibrated by the Android OS. The bias instability and velocity/angle random walk for smartphone sensors was previously analyzed by us using the Allan variation [ 14 ]. The bias instabilities are (7.3, 8.2, 8) × 10 −4 m/s 2 for the x -, y - and z -axis of the accelerometer, and (1.7, 5, 7) × 10 −5 deg/s for the gyroscope.…”

“…For example, Haas et al [ 12 ] presented the so-called L-test, which includes longer walks and turning in both directions, and Galán-Mercant et al [ 13 ] presented a 10 m version of the TUG test. Earlier, we proposed an even longer (extended) version of the TUG test (13 m long, which returns around 20 steps in one direction) to provide a more precise view of a self-paced walk at a comfortable speed in the middle of both the Gait-Go and Gait-Come phases [ 14 ].…”

“…Typically, smartphones are secured to the trunk or lower extremities. In our earlier study, we suggested a method of reconstruction of the head trajectory in 3D-space using the IMU-based accelerometer and gyroscope of a smartphone, which was fixed on a subject’s head [ 14 ]. We assumed that, in accordance with the concept of the “inverted pendulum model”, the head produces the biggest displacement in the vertical axis [ 25 ].…”

Wearable Devices for Gait Analysis in Intelligent Healthcare

“…Reginya et al applied a smartphone with accelerometers and gyroscopes to detect individuals with Parkinson's disease (PD). They analyzed the amplitude and spectrum parameters from acceleration signal and rotation speed during a conventional neurologic walking test to find the difference between individuals with and without PD (Reginya et al, 2019). Kwon et al proposed unsupervised learning algorithms using a smartphone to distinguish patient activities in the room.…”

A data process of human knee joint kinematics obtained by motion-capture measurement

“…By measuring the lower limbs of healthy volunteers of a certain species, the anatomical characteristics and movement parameters of the knee were obtained, which can provide reference for the design and optimization of artificial knee prosthesis in line with the characteristics of this species. With the development of motion capture technology [4][5][6], some scholars carry out motion capture measurement of human gait [7][8][9], some scholars have made motion capture measurement and analysis of human knee joint squatting [10][11], and some scholars use the motion capture system to measure and analyze the motion characteristics of the lower extremity joints during the stair climbing process [12][13][14][15]. Most of them use the commercial motion capture systems such as Visual3D(C-Motion, USA)and Vicon (Oxford Metrics Limited, UK) to calculate and analyze the kinematic parameters of the human knee joint; these methods need to be manually processed one by one, which are time-consuming and labor-intensive [16].…”