Portable measurement system of vertical jump using an Inertial Measurement Unit and pressure sensors

2016 ◽  
Author(s):  
M. Rico Garcia ◽  
L.-J. Morantes Guzman ◽  
J.-S. Botero Valencia ◽  
V. Madrid Henao
Keyword(s):  
Measurement System ◽  
Inertial Measurement Unit ◽  
Vertical Jump ◽  
Pressure Sensors ◽  
Measurement Unit ◽  
Inertial Measurement

scholarly journals Early Detection of Freezing of Gait during Walking Using Inertial Measurement Unit and Plantar Pressure Distribution Data

Sensors ◽  
2021 ◽  
Vol 21 (6) ◽  
pp. 2246
Author(s):  
Scott Pardoel ◽  
Gaurav Shalin ◽  
Julie Nantel ◽  
Edward D. Lemaire ◽  
Jonathan Kofman
Keyword(s):  
Early Detection ◽  
Plantar Pressure ◽  
Inertial Measurement Unit ◽  
Binary Classification ◽  
Freezing Of Gait ◽  
Pressure Sensors ◽  
Measurement Unit ◽  
Distribution Data ◽  
Inertial Measurement ◽  
Plantar Pressure Distribution

Freezing of gait (FOG) is a sudden and highly disruptive gait dysfunction that appears in mid to late-stage Parkinson’s disease (PD) and can lead to falling and injury. A system that predicts freezing before it occurs or detects freezing immediately after onset would generate an opportunity for FOG prevention or mitigation and thus enhance safe mobility and quality of life. This research used accelerometer, gyroscope, and plantar pressure sensors to extract 861 features from walking data collected from 11 people with FOG. Minimum-redundancy maximum-relevance and Relief-F feature selection were performed prior to training boosted ensembles of decision trees. The binary classification models identified Total-FOG or No FOG states, wherein the Total-FOG class included data windows from 2 s before the FOG onset until the end of the FOG episode. Three feature sets were compared: plantar pressure, inertial measurement unit (IMU), and both plantar pressure and IMU features. The plantar-pressure-only model had the greatest sensitivity and the IMU-only model had the greatest specificity. The best overall model used the combination of plantar pressure and IMU features, achieving 76.4% sensitivity and 86.2% specificity. Next, the Total-FOG class components were evaluated individually (i.e., Pre-FOG windows, Freeze windows, transition windows between Pre-FOG and Freeze). The best model detected windows that contained both Pre-FOG and FOG data with 85.2% sensitivity, which is equivalent to detecting FOG less than 1 s after the freeze began. Windows of FOG data were detected with 93.4% sensitivity. The IMU and plantar pressure feature-based model slightly outperformed models that used data from a single sensor type. The model achieved early detection by identifying the transition from Pre-FOG to FOG while maintaining excellent FOG detection performance (93.4% sensitivity). Therefore, if used as part of an intelligent, real-time FOG identification and cueing system, even if the Pre-FOG state were missed, the model would perform well as a freeze detection and cueing system that could improve the mobility and independence of people with PD during their daily activities.

scholarly journals Can IMU Provide an Accurate Vertical Jump Height Estimate?

2021 ◽  
Vol 11 (24) ◽  
pp. 12025
Author(s):  
Stefan Marković ◽  
Milivoj Dopsaj ◽  
Sašo Tomažič ◽  
Anton Kos ◽  
Aleksandar Nedeljković ◽  
...  
Keyword(s):  
Inertial Measurement Unit ◽  
Vertical Jump ◽  
Force Plate ◽  
Measurement Unit ◽  
Jump Height ◽  
Inertial Measurement ◽  
National Team ◽  
Height Estimate ◽  
Vertical Jump Height ◽  
High Level

The aim of the present study was to determine if an inertial measurement unit placed on the metatarsal part of the foot can provide valid and reliable data for an accurate estimate of vertical jump height. Thirteen female volleyball players participated in the study. All players were members of the Republic of Serbia national team. Measurement of the vertical jump height was performed for the two exemplary jumping tasks, squat jump and counter-movement jump. Vertical jump height estimation was performed using the flight time method for both devices. The presented results support a high level of concurrent validity of an inertial measurement unit in relation to a force plate for estimating vertical jump height (CMJ t = 0.897, p = 379; ICC = 0.975; SQJ t = −0.564, p = 0.578; ICC = 0.921) as well as a high level of reliability (ICC > 0.872) for inertial measurement unit results. The proposed inertial measurement unit positioning may provide an accurate vertical jump height estimate for in-field measurement of jump height as an alternative to other devices. The principal advantages include the small size of the sensor unit and possible simultaneous monitoring of multiple athletes.

scholarly journals Physical Extraction and Feature Fusion for Multi-Mode Signals in a Measurement System for Patients in Rehabilitation Exoskeleton

Sensors ◽  
2018 ◽  
Vol 18 (8) ◽  
pp. 2588 ◽  
Author(s):  
Canjun Yang ◽  
Qianxiao Wei ◽  
Xin Wu ◽  
Zhangyi Ma ◽  
Qiaoling Chen ◽  
...  
Keyword(s):  
Data Acquisition ◽  
Real Time ◽  
Measurement System ◽  
Inertial Measurement Unit ◽  
Feature Fusion ◽  
Effective Control ◽  
Measurement Unit ◽  
Individual Measurement ◽  
Visual Measurement ◽  
Inertial Measurement

Measurement system of exoskeleton robots can reflect the state of the patient. In this study, we combined an inertial measurement unit and a visual measurement unit to obtain a repeatable fusion measurement system to compensate for the deficiencies of the single data acquisition mode used by exoskeletons. Inertial measurement unit is comprised four distributed angle sensors. Triaxial acceleration and angular velocity information were transmitted to an upper computer by Bluetooth. The data sent to the control center were processed by a Kalman filter to eliminate any noise. Visual measurement unit uses camera to acquire real time images and related data information. The two data acquisition methods were fused and have its weight. Comparisons of the fusion results with individual measurement results demonstrated that the data fusion method could effectively improve the accuracy of system. It provides a set of accurate real-time measurements for patients in rehabilitation exoskeleton and data support for effective control of exoskeleton robot.

scholarly journals Pendeteksi Sikap pada Model Wahana Terbang menggunakan Inertial Measurement Unit

2015 ◽  
Vol 3 (1) ◽  
pp. 16
Author(s):  
NANDANG TARYANA ◽  
DECY NATALIANA ◽  
ALFIE RIZKY ANANDA
Keyword(s):  
Standard Deviation ◽  
Measurement System ◽  
Tilt Angle ◽  
Inertial Measurement Unit ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Model Aircraft

ABSTRAKPenelitian ini membahas tentang aplikasi dari sensor gyroscope dan accelerometer yang merupakan komponen penyusun alat ukur inersial (inertial measurement unit) untuk mendeteksi sikap (attitude) pada wahana terbang tanpa awak. Sikap (attitude) memberikan 3 (tiga) informasi yaitu roll, pitch dan yaw. Penelitian ini bertujuan untuk melihat apakah alat pendeteksi sikap (attitude) sudah layak atau tidak digunakan pada wahana terbang yang akan di-modelkan yaitu dengan cara merancang sistem pengukuran/pendeteksi serta monitoring sikap (attitude) menggunakan software LabVIEW. Metode yang digunakan untuk mendeteksi kemiringan attitude merupakan pengabungan hasil pengukuran dari gyroscope dan accelerometer. Pengujian alat pendeteksi sikap dilakukan dengan cara mensimulasikan kinematika pergerakan wahana terbang. Berdasarkan hasil pengujian, alat pendeteksi sikap sudah layak digunakan pada wahana terbang Hal ini sesuai dengan simpangan rata – rata yang diperoleh dari hasil pengukuran rotasi pada sumbu x (roll) sebesar 0,58 o, rotasi pada sumbu y (pitch) sebesar 0,53 o dan rotasi pada sumbu z (yaw) sebesar 7,64 o.Kata kunci:  Gyroscope, Accelerometer, Inertial Measurement Unit, attitude ABSTRACTThis journal elaborate the aplication of a gyroscope and accelerometer from an inertial measurement unit (IMU) for sensing attitude on an aircraft. Attitude give 3 (three) basic informations, that information are roll, pitch and yaw. The purpose of this journal is to analys if the attitude sensing device are suitble to be used on a model aircraft. This journal are designing measurement system and monitoring using software from LabVIEW. The method used to detect roll, pitch and yaw is combination from the measurement of gyroscope and accelerometer. The testing of the attitude sensing device by simulating the kinematics of an aircraft. The results shows that the attude sensing device are qualified for sensing tilt angle for x-axis (roll) with standard deviation 0,58 o, sensing tilt angle for y-axis (pitch) with standard deviation 0.53 o and sensing tilit angle for z (axis) with standar deviation 7,64 o.Keyword:  Gyroscope, Accelerometer, Inertial Measurement Unit, attitude  

scholarly journals Embedded inertial measurement unit reveals pole lean angle for cross-country skiing

2020 ◽  
Vol 23 (1) ◽  
Author(s):  
John Bruzzo ◽  
Noel C. Perkins ◽  
Aki Mikkola
Keyword(s):  
Measurement System ◽  
Inertial Measurement Unit ◽  
Angular Rate ◽  
Measurement Unit ◽  
Inertial Measurement ◽  
Lean Angle ◽  
Cross Country Skiing ◽  
Cross Country ◽  
Mean Differences ◽  
Mean Square Errors

AbstractThis study introduces an inertial measurement unit-based measurement system for resolving the dynamic lean angle of a ski pole during double poling while cross-country skiing. The measurement system estimates both the pole lean angle and pole–terrain contact events. Reported are results from 20 trials providing validated estimates of ski pole lean angle and the timing of pole plant and pole lift events. The pole lean angle is estimated from a complementary filter that fuses estimates of orientation from the embedded accelerometer and angular rate gyro. Validation follows from comparison with video capture measurements. Bland–Altman analysis showed agreement between the two measurement modalities with less than 5% bias in the mean differences (relative to the lean angle range of motion). Companion correlation analysis confirms strong correlation ($$r = 0.99$$ r = 0.99 ) between the inertial measurement unit and video-estimated lean angles and with mean root-mean-square errors below 4.5$$^{\circ }$$ ∘ .

scholarly journals Development of a Wireless Inertial Measurement System for Pitching Motion Analysis

2011 ◽  
Vol 2-3 ◽  
pp. 452-457 ◽  
Author(s):  
Seiji Kitamura ◽  
Koichi Sagawa ◽  
Toshiaki Tsukamoto ◽  
Yasuyuki Ishibashi
Keyword(s):  
Angular Velocity ◽  
Measurement System ◽  
Flash Memory ◽  
Inertial Measurement Unit ◽  
Three Dimensional ◽  
Lithium Ion ◽  
Measurement Procedure ◽  
Joint Torque ◽  
Measurement Unit ◽  
Inertial Measurement

This paper presents a wireless inertial measurement system to analyze three- dimensional (3D) pitching movement of baseball. Developed wireless inertial measurement unit (WIMU) sizes 43.7×45.2×25.7 [mm], weighs 48 [g] including Lithium-Ion battery, and consists of two types of 3D accelerometers, two types of 3D gyroscopes, release sensor, a microcontroller (MCU), flash memory, and an RF module. Synchronization of start and completion of measurement procedure for plural WIMUs are wirelessly controlled by a host computer. Three-dimensional pitching form of upper limb and trunk is produced by the numerical integration of the acceleration and angular velocity. The experimental results show that 3D posture, trajectory and joint torque in overhand and sidearm throwing are successfully estimated using the proposed system.

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