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Smartphone Technology for Mobile Motion Capture of Ergonomics Data

04 March 2013

Georgia Tech Research Institute

Ergonomics continues to play an important role in the poultry industry’s ongoing efforts to improve worker safety and health, write Sim Harbert and Linda Harley for PoultryTech.

While the industry has made significant gains in worker safety over the years, it is vital that researchers continue to develop tools and instruments specifically for poultry processing-related tasks and environments.

Ergonomists use survey instruments to evaluate human movement; however, these qualitative instruments may not correlate with quantitative measurements because of human subjectivity. The literature recommends that workers be assessed by combining qualitative and quantitative instruments to obtain a comprehensive view of their motion and posture. Traditional motion capture systems are ill suited as quantitative instruments in poultry processing environments due to hardware and calibration constraints, size and portability, and the expertise required to use them. In-plant motion tracking systems should be user-friendly, self-contained, portable, unobtrusive, and not interfere with or be degraded by plant machinery or processes.

The Georgia Tech Research Institute’s Food Processing Technology Division (FPTD) demonstrated in a proof-of-concept study that it is feasible to use Wiimotes as sensors to collect motion data from participants performing a simulated poultry plant lifting task. Wiimotes contain solid state accelerometers and rate gyros that are transmitted wirelessly to provide translation and rotation information. Currently, FPTD is developing MiMiC (Mobile Motion Capture), a smartphone application that wirelessly collects and stores movement data from kinematic modules that contain sensors similar to Wiimotes. This system will initially collect data from modules made by the Shimmer Corporation that relay accelerometer, rate gyro, and magnetic compass data over Bluetooth. The modules are housed in a small, lightweight enclosure.

The goals of the MiMiC system are that it be affordable, versatile, and mobile. But most important, it must be useful in real-life environments, with the ability to be worn by workers performing their day-to-day jobs in the processing plant and in other locations such as grow-out houses or feed mills. The very small Shimmer modules with integrated batteries allow the modules to be easily worn by workers with little interference with their normal work movement. Currently, the components are not waterproof, but this should not be an issue even in poultry processing environments, because workers will wear clothing over the smartphone and modules and not subject the components to wash-down procedures.

The versatility of the MiMiC system will allow it to use a number of different “plug-n-play” modules, including Wiimotes, Shimmer modules that include kinematic and ECG/EMG alternatives, as well as other Bluetooth modules. The ability to choose the more affordable Wiimotes that cost $50 each rather than $500 Shimmer modules would make the system more useful when affordability is important and the data precision requirements are not as stringent.

The use of a smartphone as the data collection center for the MiMiC system will keep the system lightweight and relatively small, while still providing the data storage, user interaction, and communications capabilities that are needed to make the system useful. With the communications capabilities of the smartphone, it will be possible to add the ability to upload data to remote servers for further analysis and monitoring.

The core code for MiMiC that consists of the data collection portion will be made open source to allow other researchers to make enhancements. This code will be maintained by FPTD so these enhancements can be incorporated into the MiMiC software for others to use. Hopefully, MiMiC can become a core part of other research projects and work in the area of motion analysis.

Other software enhancements such as data analysis modules could be proprietary. Initial MiMiC data analysis code may include slip, trip, and fall detection. Further analysis algorithms may provide onboard analysis of the wearer’s motions, giving feedback to the wearer of such things as extreme ranges of motion that can potentially lead to strains, sprains, or worse injuries through notification tones and/or vibration of the smartphone. This immediate feedback could also be related to the performance of the worker’s actions, an assessment of a worker’s suitability to a task, or a tool for determining job rotation scheduling.

This initial effort in creating the MiMiC mobile motion capture system is meant to be the main building block of further efforts to bring motion capture into the work environment for better analysis of worker safety issues in a broad range of areas such as slip/fall detection and prediction, ergonomic stress in lifting and deboning, and even worker training. The key purpose of MiMiC is to optimize the individual’s performance — leading to increased productivity while reducing risk of injury.

January 2013

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