According to Forbes, the global population over the age of 60 is expected to reach 2 billion by 2050. For that matter, that would represent more than one-fifth of the global population. As the elderly population increases, more advanced home monitoring is required, while still allowing people to maintain personal autonomy.

This article was co-authored by Mark Sand and Keegan Garcia

According to Forbes, the global population over the age of 60 is expected to reach 2 billion by 2050. For that matter, that would represent more than one-fifth of the global population. As the elderly population increases, more advanced home monitoring is required, while still allowing people to maintain personal autonomy. According to the U.S. Centers for Disease Control and Prevention, nearly a quarter of older adults fall each year, and falls are the leading cause of trauma hospitalization among older adults, as shown in Figure 1. Fall detection systems can use sensor-driven solutions to provide non-contact, non-privacy intrusive sensing with accurate point cloud data.

Contactless Personal Gesture Detection Using Texas Instruments Millimeter-Wave Sensors
Figure 1: Texas Instruments mmWave sensors can be used for gesture detection in elderly, disabled, and emergency surveillance systems

How Texas Instruments mmWave Sensors Help Solve the Challenges of Today’s Fall Detection Systems

The Texas Instruments IWR6843 mmWave sensor enables highly accurate fall detection without the need for contact with the person being monitored. In addition to sensing through materials, the sensor detects in all lighting conditions and provides data parameters for range, angle and velocity systems in the scene by leveraging 3D point cloud information.

Here we have Texas Instruments’ “Detect Human Falls and Pose” demo, showcasing TI’s 60 GHz IWR6843 single-chip sensor and its ability to detect a person’s height and posture when the sensor is mounted on a wall.The IWR6843 is used because the 60GHz band has been opened globally for industrial RF sensing applications

The demo uses the IWR6843ISK-ODSEVM with 120 degrees in azimuth and elevation. In this demonstration, the EVM was installed at a height of 6.5 feet, and the wide field of view helps to increase visibility to the ground and minimize dead spots. The demo can also be modified to use Texas Instruments’ IWR6843AOPEVM antenna-on-package EVM.

Figure 2 shows the 3D point cloud information. This information enables the system to analyze individual height and pose through the shape and color of the point cloud without revealing identifiable information. Note: The difference in the contours of the point cloud in the figure indicates the pose of the person.

Contactless Personal Gesture Detection Using Texas Instruments Millimeter-Wave Sensors
(a) (b) (c)

Figure 2 is a comparison of various point cloud screenshots and the photo below: (a) blue dots: horizontal profile representing a person lying down (b); blue and green dots: spherical profile representing a sitting person (c); blue dots Dots, Green Dots, and Yellow Dots: Long vertical silhouettes representing the standing posture of the person

Comparing Figure 2c with Figure 2a, it can be seen that the point cloud formation has changed. Standing persons are usually shown as elongated clusters, while lying down persons are shown as short, wide clusters. Algorithms can use this point cloud’s shape, size, and color information to detect a person’s pose and recognize their falls. The sensor observes a fall whenever there is a sudden negative change in height (z-dimension for this demo) and a sudden change in posture. Posture changes are detected when the z parameter changes from poses much larger than x (length) and y (width) to much smaller than y, indicating a rapid transition from standing to lying down states.

Remote contactless gesture detection

Many current senior alert systems require the user to press a button to trigger a response, but it is not possible to press a button if they are unconscious due to a fall. With Texas Instruments mmWave sensors, the system can detect potential falls and trigger a response, eliminating the need for individuals to constantly carry a safety alert button.

Enable non-intrusive fall detection

When Texas Instruments mmWave sensors are used as the only technology in the system, it provides more flexibility for the physical pose of the system in the home or building. Because mmWave technology captures point cloud data rather than images, fall detection systems based on mmWave technology can be used in more sensitive areas, such as bathrooms or bedrooms at home. The sensor also detects through plastic and plasterboard, allowing it to be discreetly laid out and allow for a more streamlined home design.

Rich point cloud data for accurate measurement

For elderly monitoring systems, high resolution is necessary to distinguish the posture and height of a person in a normal state. Millimeter-wave sensors from Texas Instruments output 3D point clouds and velocity information that can help determine if a person has fallen.

in conclusion

Texas Instruments mmWave sensors are smart solutions for home monitoring systems that can be used for elderly monitoring and emergencies. When used in a fall detection system, Texas Instruments’ IWR6843 provides high-accuracy monitoring while maintaining personal privacy and robustness in all environmental conditions without the need for a wearable device.

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