Imagimob Announces tinyML for Fall Detection and Gesture Recognition Applications using Texas Instruments mmWave Radar Sensors

By Tiera Oliver

Associate Editor

Embedded Computing Design

May 11, 2022


Imagimob Announces tinyML for Fall Detection and Gesture Recognition Applications using Texas Instruments mmWave Radar Sensors

Imagimob announced tinyML for two new applications based on mmWave radar sensors from Texas Instruments for fall detection and gesture recognition.

The fall detection algorithm uses a low-cost, low-power radar sensor placed on the wall in a room or an appliance, and the tinyML will detect if a person in the room falls down. The gesture recognition application recognizes 6 different predefined gestures that can be used for human machine interface in automotive and industrial settings.

Fall detection adds value to different appliances and products by adding health monitoring benefits. It can be used in products inside nursing homes, factories, or personal homes. 

Gesture recognition enables functionality with a touchless interface. Traditional interfaces require buttons / surfaces which take space and physical touch to provide inputs. This also results in breakdowns due to wear and tear and requires cleaning. Instead, one can use a compact radar and gesture recognition application to eliminate the hassle while also  activating the functionality from a distance.

The applications are supported by the two companies using the Imagimob tinyML platform and IWR6843 mmWave radar from Texas Instruments. The purpose of the applications is to give customers a head-start and shorten the time to make the applications production-ready.

A user can download Imagimob AI for free from the Imagimob website, and the two applications are included in the platform as starter projects. The user can be up and running in minutes for developing and testing applications. TI mmWave evaluation boards for IWR6843 and IWR6843AOP are also available for purchase.

Imagimob AI is a tinyML end-to-end development platform for machine learning on edge devices. It allows developers to go from data collection to deployment on an edge device in minutes. Imagimob AI is used to build production-ready models for a range of use cases including Sound Event Detection, audio, gesture recognition, human motion, predictive maintenance, material detection, and more.

Imagimob will demonstrate the applications at Embedded World 2022, Hall 4, Stand 133 that is held on June 21-23 in Nuremburg, Germany.

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Tiera Oliver, Associate Editor for Embedded Computing Design, is responsible for web content edits, product news, and constructing stories. She also assists with newsletter updates as well as contributing and editing content for ECD podcasts and the ECD YouTube channel. Before working at ECD, Tiera graduated from Northern Arizona University where she received her B.S. in journalism and political science and worked as a news reporter for the university’s student led newspaper, The Lumberjack.

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