Amazon Technologies, Inc.

Steven Sensarn

Haithem Albadawi

Miro Yakov Shverdin

Pradeep Kumar Govindaraju

Savaskan Bulek

Vashishtha Rajendra Patil

Feross Salameh

Samuel Marc Denton

Chaitra Hegde

Systems and methods for motion tracking and image capture using a stylus device are described. Example embodiments involve a stylus device outputting/emitting light on a surface and receiving backscattered light at an event sensor of the stylus device. The event sensor may generate event data based in part on intensity of the received backscattered light. The stylus device may perform a motion tracking and/or image capture operation based on the event data.

Motion tracking and image capturing using stylus devices

Techniques for detecting user activity and repetitions (rep) counting are described. A system may dynamically determine a threshold value for counting reps. The threshold value may be based on an activity predicted by the system using sensor data. The threshold value may be based on a rep rate. Changes in the threshold value may enable more accurate rep counting when a user is performing an activity that involves taking reps, such as, walking, running, rowing bicycling, etc., and may further cease counting of reps when a user is performing an activity that does not involve taking repetitions but may result in sensor data that triggers rep counting.

Activity classification and repetition counting

A device that is capable of performing tap detection and other gesture detection using data from an accelerometer. Motion data from the accelerometer is filtered and processed to detect motion. If motion is detected filtered motion data may be processed using a first neural network to detect a tap gesture, which may include one or multiple taps. Motion data may also be processed using a second neutral network to detect other gestures, which may be turned on or off based on a location of the device. Actions may be performed in response to a detected gesture, where the action may be performed by the device or by another device or system.

Tap and gesture detection using accelerometer data

A system configured to detect a tap event on a surface of a device using microphone audio data and motion data. Instead of using a physical sensor to detect the tap event, the device detects a tap event based on a power level difference between two or more microphones. When a power ratio exceeds a threshold, the device may detect a tap event and perform an action, such as delaying or ending an alarm. To reduce false positives caused by wind or loud noises close to the microphones, the device may confirm a tap event using motion data that indicates actual movement of the device. In some examples, the device may detect the tap event using a neural network processing the microphone data and the motion data. In addition, the device may embed the motion data within the microphone data using unused bits of the microphone data.

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Milpitas, CA, United States of America

Steven Sensarn