scholarly journals Lossless Compression of Human Movement IMU Signals

Sensors ◽  
2020 ◽  
Vol 20 (20) ◽  
pp. 5926
Author(s):  
David Chiasson ◽  
Junkai Xu ◽  
Peter Shull
Keyword(s):  
Lossless Compression ◽  
Human Movement ◽  
Measurement Unit ◽  
Compression Method ◽  
Efficient Manner ◽  
Fixed Point Computation ◽  
Movement Data ◽  
Optimal Linear ◽  
Traditional Representation ◽  
Movement Activities

Real-time human movement inertial measurement unit (IMU) signals are central to many emerging medical and technological applications, yet few techniques have been proposed to process and represent this information modality in an efficient manner. In this paper, we explore methods for the lossless compression of human movement IMU data and compute compression ratios as compared with traditional representation formats on a public corpus of human movement IMU signals for walking, running, sitting, standing, and biking human movement activities. Delta coding was the highest performing compression method which compressed walking, running, and biking data by a factor of 10 and compressed sitting and standing data by a factor of 18 relative to the original CSV formats. Furthermore, delta encoding was shown to approach the a posteriori optimal linear compression level. All methods were implemented and released as open source C code using fixed point computation which can be integrated into a variety of computational platforms. These results could serve to inform and enable human movement data compression in a variety of emerging medical and technological applications.

scholarly journals Variation in human mobility and its impact on the risk of future COVID-19 outbreaks in Taiwan

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Meng-Chun Chang ◽  
Rebecca Kahn ◽  
Yu-An Li ◽  
Cheng-Sheng Lee ◽  
Caroline O. Buckee ◽  
...  
Keyword(s):  
Disease Surveillance ◽  
Initial Conditions ◽  
Human Mobility ◽  
Human Movement ◽  
Disease Spread ◽  
Spatial Spread ◽  
Movement Data ◽  
Intercity Travel ◽  
Travel Restrictions ◽  
The Impact

Abstract Background As COVID-19 continues to spread around the world, understanding how patterns of human mobility and connectivity affect outbreak dynamics, especially before outbreaks establish locally, is critical for informing response efforts. In Taiwan, most cases to date were imported or linked to imported cases. Methods In collaboration with Facebook Data for Good, we characterized changes in movement patterns in Taiwan since February 2020, and built metapopulation models that incorporate human movement data to identify the high risk areas of disease spread and assess the potential effects of local travel restrictions in Taiwan. Results We found that mobility changed with the number of local cases in Taiwan in the past few months. For each city, we identified the most highly connected areas that may serve as sources of importation during an outbreak. We showed that the risk of an outbreak in Taiwan is enhanced if initial infections occur around holidays. Intracity travel reductions have a higher impact on the risk of an outbreak than intercity travel reductions, while intercity travel reductions can narrow the scope of the outbreak and help target resources. The timing, duration, and level of travel reduction together determine the impact of travel reductions on the number of infections, and multiple combinations of these can result in similar impact. Conclusions To prepare for the potential spread within Taiwan, we utilized Facebook’s aggregated and anonymized movement and colocation data to identify cities with higher risk of infection and regional importation. We developed an interactive application that allows users to vary inputs and assumptions and shows the spatial spread of the disease and the impact of intercity and intracity travel reduction under different initial conditions. Our results can be used readily if local transmission occurs in Taiwan after relaxation of border control, providing important insights into future disease surveillance and policies for travel restrictions.

A new lossless compression method using Direction Adaptive-Discrete wavelet transform and Modified SPIHT coding

2021 ◽  
Author(s):  
N. Karthika Devi ◽  
G. Mahendran ◽  
S. Murugeswari ◽  
S. Praveen Samuel Washburn ◽  
D. Archana Devi ◽  
...  
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Lossless Compression ◽  
Discrete Wavelet ◽  
Compression Method ◽  
Spiht Coding

An Improved and Efficient Algorithm for SINS/GPS/Doppler Integrated Navigation Systems

2012 ◽  
Vol 245 ◽  
pp. 323-329 ◽  
Author(s):  
Muhammad Ushaq ◽  
Jian Cheng Fang
Keyword(s):  
Kalman Filter ◽  
Navigation System ◽  
Inertial Navigation System ◽  
Inertial Sensor ◽  
Inertial Navigation ◽  
Measurement Unit ◽  
Navigation Systems ◽  
Integrated Navigation ◽  
Efficient Manner ◽  
Position Errors

Inertial navigation systems exhibit position errors that tend to grow with time in an unbounded mode. This degradation is due, in part, to errors in the initialization of the inertial measurement unit and inertial sensor imperfections such as accelerometer biases and gyroscope drifts. Mitigation to this growth and bounding the errors is to update the inertial navigation system periodically with external position (and/or velocity, attitude) fixes. The synergistic effect is obtained through external measurements updating the inertial navigation system using Kalman filter algorithm. It is a natural requirement that the inertial data and data from the external aids be combined in an optimal and efficient manner. In this paper an efficient method for integration of Strapdown Inertia Navigation System (SINS), Global Positioning System (GPS) and Doppler radar is presented using a centralized linear Kalman filter by treating vector measurements with uncorrelated errors as scalars. Two main advantages have been obtained with this improved scheme. First is the reduced computation time as the number of arithmetic computation required for processing a vector as successive scalar measurements is significantly less than the corresponding number of operations for vector measurement processing. Second advantage is the improved numerical accuracy as avoiding matrix inversion in the implementation of covariance equations improves the robustness of the covariance computations against round off errors.

Arm Movement Analysis in Human Daily Life for Improving Durability of Artificial Elbow Joint

2020 ◽  
Author(s):  
Chihiro Kamio ◽  
Tatsuhito Aihara ◽  
Gaku Minorikawa
Keyword(s):  
Daily Life ◽  
Human Life ◽  
Arm Movement ◽  
Movement Analysis ◽  
Human Movement ◽  
Healthcare Applications ◽  
Artificial Joints ◽  
Measuring Device ◽  
Movement Data ◽  
Set Up

Abstract Human movement data can contribute to the quality improvement of industrial and medical products affected by such movement. Such data can be used to improve the quality of industrial products as well as in healthcare applications, such as the development of artificial joints. To develop and design artificial joints with enhance durability, it is necessary to set up standards of durability using human movement data in daily life. The aim of this study is to obtain data that contributes to the improvement in durability of artificial elbow joints. We have developed a wearable device that can measure its self-acceleration, angular velocity, and quaternions to collect human movement data continuously for long-term. Additionally, we collected the arm movement data of 30 participants using the developed device. The participants of this study carried on with their normal lives with the measuring device worn on their wrist. This study calculated the posture of the wrist over time using quaternions and mainly analyzed posture changes. We clarified the characteristics and trends of the movement of bending the elbow in daily human life.

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