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Ergonomic Box-Lifting Wearable

Today is the last day at CES and we would like to highlight the box lifting wearable demo in the SensiML suite.

According to the Bureau of Labor Statistics (BLS), more than one million workers experience back injuries each year. One-fourth of all worker compensation indemnity claims are a result of back injuries. In this demonstration, we show how the SensiML Analytics Toolkit Suite detects the more subtle nuances in time-series motion data. We are showcasing how we can distinguish proper versus improper form or proper lifting techniques for a worker lifting a box.

When you consider the number of warehouses, factories, and field workers who are at risk for potential back injuries and worker’s compensation claims due to preventable poor lifting techniques, the proper dos and don’ts of such an application become clear.  With SensiML Analytics Toolkit, innovative wearable IoT device vendors can easily build accurate ergonomic models capable of distinguishing proper form for training and/or compliance.  This application was built within two weeks using captured sensor data and SensiML automated algorithm generation.

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