Using LabVIEW and Wireless Gyroscopes to Detect Periodical Gait Events

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"The LabVIEW Advanced Signal Processing Toolkit simplified the development process and reduced the time it took to design and develop this system."

- Darwin Gouwanda, Monash University Sunway campus

The Challenge:
Acquiring measurement data from wireless gyroscopes in real time and developing a method that periodically identifies gait events such as heel-strike and toe-off during walking to determine the duration of one gait cycle, which includes one stance phase and one swing phase, during walking.

The Solution:
Using NI LabVIEW software to develop a gait monitoring system that transmits real-time data about a subject’s walking pattern between the wireless gyroscopes and the workstation.

Author(s):
Darwin Gouwanda - Monash University Sunway campus
Arosha Senanayake - Monash University Sunway campus

Abstract

Walking is one of the most common human activities. Although it may seem trivial, walking is a complex and repetitive process that requires the coordination of the lower limbs to move forward and maintain body balance with one foot in contact with the ground at all times. This repetitive process is generally referred to as a gait cycle where gait implies the human walking pattern. Acute injury to one of the limbs can disrupt this process and cause abnormal gait. Significant differences between normal and abnormal gait can be found in the duration of a stride, stance phase, and swing phase. To quantify these parameters, we developed a wireless gyroscope-based gait monitoring system.

The Gait Monitoring System

Gait is a repetitive process. It starts with heel-strike and ends with a subsequent heel-strike of the same foot. A gait cycle consists of two major phases: the stance phase and the swing phase. The stance phase is a period when the foot is in contact with the ground. It begins with a heel-strike and ends with a toe-off of the same foot. Swing phase is a period when the foot lifts off the ground. It starts with toe-off and ends with a subsequent heel-strike of the same foot. The duration of one gait cycle, the stance phase and swing phase, hold important roles in diagnosing and tracking the rehabilitation progress of patients with pathologic conditions, patients who undergo medical treatment or surgery, and patients who use a prosthetic limb or functional electrical stimulation system (FES).

As a solution, we proposed a gait monitoring system that uses wireless gyroscopes (Figure 1). This system has two main objectives. First, it has to measure the angular rates of the lower limbs in real time and record the measurement data in a spreadsheet file. Second, it has to identify the heel-strike and toe-off of the left and right limb and quantify the duration of one gait cycle. It is important to mention that the occurrences of heel-strike and toe-off can be found in a shank angular rate.

To achieve these objectives, we selected LabVIEW as the system development platform. LabVIEW not only helped us to develop a user-friendly GUI, but it also enabled us to collect simultaneous real-time data streaming from two wireless gyroscopes and send it to the workstation. Using the LabVIEW Advanced Signal Processing Toolkit also shortened the development time and reduced the tedious programming work because it offers comprehensive signal processing tools and algorithms.

The Software Architecture

The gait monitoring system uses two wireless gyroscopes to measure the angular rate of the shanks. While a person is walking, the gyroscopes measure the angular rates and transmit them to the workstation in real time. Once the workstation receives the measurement data, the data is displayed on the running charts. At the same time, data is stored in a temporary buffer. Measurement data is kept for 5 seconds. Every 5 seconds, the angular rate of the shank is processed using the LabVIEW Advanced Signal Processing Toolkit to identify the heel-strike and toe-off. The occurrences of these events are then used to estimate the duration of one gait cycle, stance phase, and swing phase.

This system offers several additional functionalities. One of the functionalities is report generation. After the experiment is complete, the user can produce an HTML-based report that contains the experiment details, subject’s details, and the experimental results. If the user wishes to keep the measurement data for future reference, he or she can choose to save it along with the subject and experiment details in a spreadsheet file (*.csv). Other additional functionalities include the communication check between the workstation and the wireless transceivers and the communication check between the transceivers and the respective gyroscope.

Experimental Study

To examine the performance of the proposed system, we simulated abnormal gait by placing a 2.5 Kg load on the lower shank. Loading one side of the limbs changes the inertial property of the loaded limb, hence, it alters the gait spatio-temporal parameters. Figure 3 presents a set of experimental results compiled from this study. Even though the waveforms were slightly different in treadmill and ground walking, the gait events identification algorithm successfully identified the heel-strikes and toe-offs. More importantly, it did not disrupt the real-time data acquisition. Measurement data transmitted by the gyroscopes was still received by the workstation and continuously displayed on the running charts as depicted in Figure 1.

Conclusion

We used LabVIEW to develop all the functionalities available in this system. It streams real-time data from the wireless gyroscopes to the workstation and also provides an intuitive and user-friendly GUI so an operator who does not have much experience using this system can obtain the necessary parameters that characterize a person’s walking condition. More importantly, the signal processing tools available in the LabVIEW Advanced Signal Processing Toolkit simplified the development process and reduced the time it took to design and develop this system. The experimental study validated the efficacy of the system in identifying the heel-strike and toe-off in different walking conditions. It also further demonstrated the capability of LabVIEW in providing a reliable platform to acquire and periodically process measurement data in real time.

Author Information:
Darwin Gouwanda
Monash University Sunway campus
Jalan Lagoon Selatan, Bandar Sunway
Selangor
Malaysia
Tel: 60123507589
darwin_gouwanda@yahoo.com

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