Drop Without Danger

Inspired by the tragic loss of a young engineer whose life and potential were cut short (sidebar, Honoring Eamonn), Sensors last year announced the launch of its Engineer of the Year award. After reading and weighing the relative merits of all submissions, the editors of Sensors decided on a winner—or rather, a group of winners. Let us tell you about the inspiration for this team's work, as well as the system and method they devised to answer the challenge.

Seeking a Solution

Portable electronic devices, including computers, PDAs, cellular phones, and music players, are often accidentally dropped, and when that happens the resulting impact can damage sensitive components. Sometimes the devices can better withstand an impact if put into a protective mode; for those that include hard drives, for instance, the drives can be parked to reduce such results as data loss or disk damage. In these devices, it is beneficial to detect when a fall is actually occurring—but fall-detection methods have heretofore had limited success. Some methods have relied upon complex angular velocity calculations, for example, and are applicable only to devices with spinning disks. Other methods have been limited in their ability to detect falls accompanied by other motions such as rotation or additional external force (e.g., a nonlinear fall).

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In an effort to solve the problem of free-fall detection that laptop computer manufacturers and others had struggled with, Freescale Semiconductor Inc.'s Inertial Sensor Applications Team—consisting of Michelle Kelsey, Leticia Gomez, Rod Borras, and Akihiro Ueda—got directly involved and went to work using lower-g (1.5 – 6 g) accelerometer products to determine how accelerometers can detect free fall, and by developing and testing free-fall software algorithms.

Michelle Kelsey
Michelle Kelsey

Evolution of the System

The Inertial Sensor Applications Team initially found an algorithm able to detect linear free fall without the need for an initial system calibration. A key physical property involved in such an algorithm is that under static conditions and normal motion, one or more of the three axes will always be affected by gravity; during a linear free-fall event, all three axes return to a "zero g" condition. By summing the squares of the three axial acceleration readings, it is possible to determine whether an object is static or moving.

Another step in the development of the algorithm was finding a way to detect rotational free-fall events, wherein many objects can fall, or be thrown, with a rotational component to the motion. Furthermore, by performing an analysis of the conditions immediately preceding a free-fall condition, it can indicate whether the corresponding object was dropped or thrown. In this way, the algorithm can reveal—for the purpose of product warranty claims, for instance—from what height an object was dropped, and whether it was mishandled.

Leticia Gomez
Leticia Gomez

The team has developed an improved system and method (patents pending) that provides fall detection in a reliable and efficient manner even in the presence of other motion. The system includes multiple accelerometers and a processor: The accelerometers provide measurements describing acceleration in all directions to the processor. The processor receives the data and compares them to a value range to determine whether the device is currently falling. If the acceleration measurement combinations are within the value range and are smooth, then a nonlinear fall is occurring. The processor then sends a signal to the device, which can take action to reduce the potential negative results of the impending impact. For example, the device can suspend operation and/or save data, thus preventing data loss if it happens to be in write mode.

Rod Borras
Rod Borras


Today, Samsung Electronics has designed the MMA7260Q 3-axis sensor (with g-select capability for 1.5 g/2 g/4 g/6 g sensitivity) into two of its newest digital audio players, the YH-J70 and YP-T8. Freescale's accelerometer enables not only free-fall detection for the MP3 players' hard disk drives, but also unique features such as menu scroll by tilt.

Akihiro Ueda
Akihiro Ueda

Other applications for the accelerometer include human body fall detection, shipping and handling monitoring, wireless sensor networking, fall and shock logging for warranty information-gathering, and black box/event recording. In addition, the devices can send an alert for help when an elderly person or public safety worker (e.g., firefighter or police officer) falls, and can also detect the body's movements after the fall.

Although inertial sensors were developed to detect shock in order to trigger airbag deployment, these devices can also be used to measure vibration, tilt, movement, and positioning, in addition to fall. As testament to this fact, the Inertial Sensor Applications Team sometimes finds, in visiting with customers to discuss particular applications, that the same device can provide at least two or three more functions, without additional hardware.

Honoring Eamonn
Honoring Eamonn

Furthering Education

To expand knowledge of accelerometer capabilities and functionalities, the Inertial Sensor Applications Team has created a development tool known as the Sensing Triple Axis Reference (STAR) board (www.sensorsmag.com/1006/EOY1~). This development tool enables multiple detection situations including, for example, free fall, tilt, motion, positioning, shock, and vibration. The STAR board features a graphical user interface that provides visualization of key accelerometer applications in the consumer, industrial, health care, and appliance industries, which adds to the body of knowledge of accelerometer functionality. The popularity of these boards has helped identify new accelerometer applications.

The team has also created an online course, The 3-Axis MMA7260Q Low g Acceleration Sensor (www.embeddedlearningcenter.com), which covers linear, rotational, and projectile measurements, plus free-fall sensing considerations such as g-range, cross-axis acceleration, and height requirements for detection.

Congratulations and thanks to Michelle, Leticia, Rod, and Akihiro for all their efforts on this ingenious application of sensor technology. May their work inspire others as Eamonn's enthusiasm inspired us.

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