Using Shimmer Sensors to Provide Biofeedback in Resistance Training
Recently a new app was released to help achieve efficient resistance training using Shimmer sensors and LabVIEW technology to create a virtual assistant. It was developed by Martin O’Reilly, a student at the National University of Ireland, Galway.
Background and Objectives
The aim of resistance training is to improve muscular strength and power, achieve muscle hypertrophy, and increase fat attrition.
However, self-monitoring is not always successful and may increase the risk of injury, or lead to slower than optimal progress towards one’s predefined targets, due to a faulty technique, while a personal trainer is out of reach for most people. As a result, there is a real need for a form of feedback which can be given in real-time during training.
The app developed by O’Reilly uses biofeedback to supply sensors with signals of inertial movement, which are processed via algorithms to yield good-quality data on various parameters of resistance training.
These include the tempo of movement, the range of movement of important parts of the body, the set and repetition counts, weight assessment, and detection of dangerous movements which are likely to cause injury.
The earliest version of this app can be used to monitor the user’s performance during three core exercise, the squat, the deadlift and the benchpress.
The system was developed with the following steps:
- Sensors and signal analysis - Data was collected via sensors, whose position was manipulated to find the proper positioned the right set of sensors for later analysis of different exercises
- Algorithm development - The algorithm set was developed with the use of matrices to calculate the joint angle and the velocity of joint movement, as well as the range of motion, along with counting sets and repetitions
- Exercise analysis in gym - The data was analyzed to determine if any movements are likely to endanger joint health, as well as to set the appropriate repetition number and the thresholds for proper range of motion exercises
- Final development of the application - The app was developed using all these parameters and data collected to provide real-time biofeedback during training, with the popup widget capable of displaying long-term progress, with the facility to save the data as an installable app which can be viewed on all Windows computers.
Integrating Shimmer and LabVIEW
The developer had much experience as a personal trainer prior to developing the present application, but he noted that it was much easier and quicker to use the Shimmer hardware in combination with LabVIEW to build this training system.
The Shimmer sensors were useful in yielding data on muscular movement which could be used efficiently using the LabVIEW Instrument Driver. The graphical method of programming was highly user-friendly, enabling ideas to be tested rapidly in the form of visuals.
Shimmer sensors could also be calibrated quickly with the Shimmer 9Dof which is a specific calibration application. Once the right sequence of charging the units and regular calibration was developed, the right type of data was readily collected to produce this system.
The flexibility required for the system to be used by all types of athletes and for various exercises was built in because it was designed to be a virtual personal trainer, that delivered live feedback for the user to improve the training sessions and achieve goals quickly and safely.
A user interface that looked good and appealed to the customer was also important, and was achieved using library resources and appropriate PNG images and other front panel objects.
System Evaluation and Testing
An initial pilot study was done using 20 subjects, of which 10 were top-class athletes and 10 were not very active in this area. While they exercised, their technique was compared both with and without the use of this feedback system. The results are displayed below:
The system developed by O’Reilly was found to be capable of giving accurate and full-scale biofeedback for resistance training, which can help the exercise subject to improve exercise technique and reduce the injury risk while reaching training goals more quickly.
At present this system is available only through LabVIEW but it is being refined by adding more features such as:
- Compatibility with smartphones
- Cloud data storage facility by optimization for servers
- Integration of aural feedback
- Addition of more exercises and goals
- Adding in more sensing parameters such as EMG to detect muscle fatigue and GSR for stress
- Adding or substituting a higher-level system to help elite athletes train better with more directed body building and isometric exercises
- Building a mobility improvement system for geriatric or elderly patients
- Designing garments which incorporate sensors to be worn over the body
Since the Shimmer technology was originally conceived in 2006, to when the company was founded in 2008, we have been pioneering wearable sensor technology and solutions, and currently ship to over 80 countries worldwide.
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