Inertial measurement unit

About: Inertial measurement unit is a research topic. Over the lifetime, 13326 publications have been published within this topic receiving 189083 citations. The topic is also known as: IMU.

A compact, high-speed, wearable sensor network for biomotion capture and interactive media

Abstract: In this paper, we present a wireless sensor platform designed for processing multipoint human motion with low latency and high resolution. One application considered here is interactive dance, in which a choreographer wishes to translate the movements of multiple dancers into real-time audio or video content to accompany the performance. This can only be accomplished using a distributed measurement system capable of responding quickly with enough information to describe the expressive movements of multiple people. Similar requirements exist for biomechanical analysis, especially in the context of athletic training, where high resolution is demanded, and instant feedback is also desirable. Our approach to addressing such aggressive requirements involves a high-speed wireless network of compact inertial measurement units (IMUs) that can be worn at various locations on the body. Each device is equipped with its own 1 Mbps radio link and a full six-axis IMU, as well as a capacitive node-to-node proximity sensor. Currently, the system supports real-time data collection and processing for up to 25 nodes with 100 Hz full state updates, thereby handling much higher data rates than its predecessors. With locally buffered data, sample rates of up to 1 kHz have been achieved successfully. Early results discussed here demonstrate the feasibility of our design through testing with both dancers and professional athletes.

Reliable Real-Time Recognition of Motion Related Human Activities using MEMS Inertial Sensors

Abstract: Knowledge about the current motion related activity of a person is information that is required or useful for a number of applications. Technical advances in the past years have reduced prices for sensors capable of providing the necessary input, in particular MEMS based inertial measurement units (IMUs). In addition to a low price, unobtrusiveness is a requirement for a activity recognition system. We achieve this by mounting one IMU to the belt of the user. In this work we present the design of our recognition system, including the features computed from the raw accelerations and turn rates as well as four different classification algorithms. These are used in Bayesian techniques trained from a semi naturalistic, labeled data set. The best classifier recognizes the activities ’Sitting’, ’Standing’, ’Walking’, ’Running’, ’Jumping’, ’Falling’ and ’Lying’ of any person with recognition recalls and precisions between 93 and 100% except for an only 80% recall rate for ’Falling’ as that suffers from its very short duration.

Vehicle positioning and data integrating method and system thereof

Abstract: A vehicle positioning and data integrating process and system can substantially solve the problems encountered in avionics system integration, which employs integrated global positioning system/inertial measurement unit enhanced with altitude measurements to derive vehicle position, velocity, attitude, and body acceleration and rotation information. A vehicle positioning and data integrating system comprises navigation sensors and an IMU interface and preprocessing board, an altitude interface and processing board, a navigation processing board, a shared memory card, a bus arbiter, a control board, and a bus interface. The control board distributes navigation data to flight management system, flight control system, automatic dependent aurveillance, cockpit display, enhanced ground proximity warning system, weather radar, and satellite communication system.