scholarly journals A Multi-Sensor Matched Filter Approach to Robust Segmentation of Assisted Gait

Sensors ◽  
2018 ◽  
Vol 18 (9) ◽  
pp. 2970 ◽  
Author(s):  
Satinder Gill ◽  
Nitin Seth ◽  
Erik Scheme
Keyword(s):  
Matched Filter ◽  
Angular Rate ◽  
Peak Detection ◽  
Segmentation Algorithm ◽  
Sensor Data ◽  
Assistive Device ◽  
Mobility Impairments ◽  
Non Invasive ◽  
Robust Segmentation ◽  
Filter Approach

Individuals with mobility impairments related to age, injury, or disease, often require the help of an assistive device (AD) such as a cane to ambulate, increase safety, and improve overall stability. Instrumenting these devices has been proposed as a non-invasive way to proactively monitor an individual’s reliance on the AD while also obtaining information about behaviors and changes in gait. A critical first step in the analysis of these data, however, is the accurate processing and segmentation of the sensor data to extract relevant gait information. In this paper, we present a highly accurate multi-sensor-based gait segmentation algorithm that is robust to a variety of walking conditions using an AD. A matched filtering approach based on loading information is used in conjunction with an angular rate reversal and peak detection technique, to identify important gait events. The algorithm is tested over a variety of terrains using a hybrid sensorized cane, capable of measuring loading, mobility, and stability information. The reliability and accuracy of the proposed multi-sensor matched filter (MSMF) algorithm is compared with variations of the commonly employed gyroscope peak detection (GPD) algorithm. Results of an experiment with a group of 30 healthy participants walking over various terrains demonstrated the ability of the proposed segmentation algorithm to reliably and accurately segment gait events.

Head acceleration measurement techniques: Reliability of angular rate sensor data in helmeted impact testing

2017 ◽  
Vol 232 (2) ◽  
pp. 176-181 ◽  
Author(s):  
Bryan R Cobb ◽  
Abigail M Tyson ◽  
Steven Rowson
Keyword(s):  
Root Mean Square ◽  
Angular Rate ◽  
Angular Acceleration ◽  
Impact Testing ◽  
Sensor Data ◽  
Mean Square ◽  
Head Acceleration ◽  
Angular Rate Sensor ◽  
Impact Tests ◽  
Rate Sensor

This study sought to evaluate the suitability of angular rate sensors for quantifying angular acceleration in helmeted headform impacts. A helmeted Hybrid III headform, instrumented with a 3-2-2-2 nine accelerometer array and angular rate sensors, was impacted (n = 90) at six locations and three velocities (3.1, 4.9, and 6.4 m/s). Data were low-pass filtered using Butterworth four-pole phaseless digital filters which conform to the specifications described in the Society of Automotive Engineers J211 standard on instrumentation for impact tests. Nine accelerometer array data were filtered using channel frequency class 180, which corresponds to a −3 db cutoff frequency of 300 Hz. Angular rate sensor data were filtered using channel frequency class values ranging from 5 to 1000 Hz in increments of 5 Hz, which correspond to −3 db cutoff frequencies of 8 to 1650 Hz. Root-mean-square differences in peak angular acceleration between the two instrumentation schemes were assessed for each channel frequency class value. Filtering angular rate sensor data with channel frequency class values between 120 and 205 all produced mean differences within ±5%. The minimum root-mean-square difference of 297 rad/s2 was found when the angular rate sensor data were filtered using channel frequency class 175. This filter specification resulted in a mean difference of 28 ± 297 rad/s2 (1.8% ± 8.6%). Condition-specific differences (α=0.05) were observed for 11 of 18 test conditions. A total of 4 of those 11 conditions were within ±5%, and 10 were within ±10%. Furthermore, the nine accelerometer array and angular rate sensor methods demonstrated similar levels of repeatability. These data suggest that angular rate sensor may be an appropriate alternative to the nine accelerometer array for measuring angular head acceleration in helmeted head impact tests with impactor velocities of 3.1–6.4 m/s and impact durations of approximately 10 ms.

scholarly journals Welfare Quality® for dairy cows: towards a sensor-based assessment

2020 ◽  
Vol 87 (S1) ◽  
pp. 28-33 ◽  
Author(s):  
Francisco Maroto Molina ◽  
Carlos C. Pérez Marín ◽  
Laura Molina Moreno ◽  
Estrella I. Agüera Buendía ◽  
Dolores C. Pérez Marín
Keyword(s):  
Dairy Cows ◽  
Dairy Farms ◽  
Assessment Method ◽  
Sensor Data ◽  
Objective Data ◽  
Livestock Farming ◽  
Precision Livestock Farming ◽  
Non Invasive ◽  
Social Concerns ◽  
Welfare Quality

AbstractThis Research Reflection addresses the possibilities for Welfare Quality® to evolve from an assessment method based on data gathered on punctual visits to the farm to an assessment method based on sensor data. This approach could provide continuous and objective data, while being less costly and time consuming. Precision Livestock Farming (PLF) technologies enabling the monitorisation of Welfare Quality® measures are reviewed and discussed. For those measures that cannot be assessed by current technologies, some options to be developed are proposed. Picturing future dairy farms, the need for multipurpose and non-invasive PLF technologies is stated, in order to avoid an excessive artificialisation of the production system. Social concerns regarding digitalisation are also discussed.

scholarly journals Catalog extraction in SZ cluster surveys: a matched filter approach

2006 ◽  
Vol 459 (2) ◽  
pp. 341-352 ◽  
Author(s):  
J.-B. Melin ◽  
J. G. Bartlett ◽  
J. Delabrouille
Keyword(s):  
Matched Filter ◽  
Filter Approach

Wireless Device Based on MEMS Sensors and Bluetooth Low Energy (LE/Smart) Technology for Diagnostics of Mechatronic Systems

2013 ◽  
Vol 460 ◽  
pp. 13-21 ◽  
Author(s):  
Kamil Židek ◽  
Alexander Hošovský
Keyword(s):  
Angular Rate ◽  
Operation Time ◽  
Low Energy ◽  
Sensor Data ◽  
Diagnostic Tools ◽  
Mems Sensors ◽  
Desktop Computer ◽  
Mechatronic Systems ◽  
Communication Interface ◽  
Wireless Device

This paper deals with usability of MEMS sensors for diagnostics of mechatronics system state wirelessly. We can acquire basic kinematics and dynamics mechanism parameters (spatial position, speed, acceleration, vibration, angular rate, orientation, etc.) and some environment condition (local/remote temperature, humidity, pressure, electromagnetic noise) by MEMS sensors. Acquired data are sent to remote application in desktop computer. This system can replace expensive and separate diagnostic tools by small integrated solution with one wireless communication interface (with limitation of MEMS sensors precision). This solution can be battery powered with long operation time, because there is used new wireless technology based on Bluetooth 4 protocol (Low Energy/Smart Bluetooth). Some of integrated MEMS sensors measures same variable on different measuring principle. For example angle can be acquired from three different sensors: magnetometer, accelerometer or gyroscope. Combination of these sensor data can significantly improve value accuracy. The designed diagnostic tool can serve as an inertia measuring unit IMU or Wireless IMU (WIMU).

scholarly journals A matched filter approach for blind joint detection of galaxy clusters in X-ray and SZ surveys

2018 ◽  
Vol 614 ◽  
pp. A82 ◽  
Author(s):  
P. Tarrío ◽  
J.-B. Melin ◽  
M. Arnaud
Keyword(s):  
Galaxy Clusters ◽  
Matched Filter ◽  
Detection Efficiency ◽  
Blind Detection ◽  
Joint Detection ◽  
Ionized Gas ◽  
X Ray ◽  
Sky Survey ◽  
Filter Approach ◽  
Using Data

The combination of X-ray and Sunyaev–Zeldovich (SZ) observations can potentially improve the cluster detection efficiency, when compared to using only one of these probes, since both probe the same medium, the hot ionized gas of the intra-cluster medium. We present a method based on matched multifrequency filters (MMF) for detecting galaxy clusters from SZ and X-ray surveys. This method builds on a previously proposed joint X-ray–SZ extraction method and allows the blind detection of clusters, that is finding new clusters without knowing their position, size, or redshift, by searching on SZ and X-ray maps simultaneously. The proposed method is tested using data from the ROSAT all-sky survey and from the Planck survey. The evaluation is done by comparison with existing cluster catalogues in the area of the sky covered by the deep SPT survey. Thanks to the addition of the X-ray information, the joint detection method is able to achieve simultaneously better purity, better detection efficiency, and better position accuracy than its predecessor Planck MMF, which is based on SZ maps alone. For a purity of 85%, the X-ray–SZ method detects 141 confirmed clusters in the SPT region; to detect the same number of confirmed clusters with Planck MMF, we would need to decrease its purity to 70%. We provide a catalogue of 225 sources selected by the proposed method in the SPT footprint, with masses ranging between 0.7 and 14.5 ×1014 M⊙ and redshifts between 0.01 and 1.2.

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