PL
 |
EN
Preferencje help
Polish version English version Język
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 9

Liczba wyników na stronie
first rewind previous Strona / 1 next fast forward last
Wyniki wyszukiwania
Wyszukiwano:
w słowach kluczowych:  inertial sensor
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 1 next fast forward last
1
Content available remote Prototypowanie modułów mikroprocesorowych do wykrywania wzorców ruchowych
Marciniak Tomasz, Marciniak Wojciech, Dąbrowski Adam
Przegląd Elektrotechniczny
|
2022
|
R. 98, nr 2
87--90
PL
W artykule przedstawiono rozwiązania mikroprocesorowych modułów elektronicznych umożliwiających eksperymentalne rozpoznawanie wzorców ruchowych na podstawie danych pochodzących z czujników inercyjnych. Pokazano rozwiązania oparte na mikrokontrolerze ATmega328P oraz bardziej zaawansowane z użyciem mikrokontrolerów STM32L476RG oraz STM32L4R9. Omówiono możliwości czujników, w tym najnowszych rozwiązań zawierających elementy uczenia maszynowego. Przedstawiono oprogramowanie wspomagające proces przygotowywania projektów.
EN
The paper presents solutions of microprocessor electronic modules that enable an experimental recognition of movement patterns on the basis of data from inertial sensors. Simple solutions based on the ATmega328P microcontroller and more advanced ones with the use of STM32L476RG and STM32L4R9 microcontrollers were shown. The possibilities of sensors were discussed, including the latest solutions containing elements of machine learning. The software supporting the project preparation process was also presented.
2
Content available Rat robot motion state identification based on a wearable inertial sensor
Chen Yuxin, Xu Haoze, Yang Wei, Yang Canjun, Xu Kedi
Metrology and Measurement Systems
|
2021
|
Vol. 28, nr 2
255--268
EN
Rat robots have great potential in rescue and search tasks because of their excellent motion ability. However, most of the current rat-robot systems relay on human guidance due to variable voluntary motor behaviour of rats, which limits their application. In this study, we developed a real-time system to detect a rat robot’s transient motion states, as the prerequisite for further study of automatic navigation. We built the detection model by using a wearable inertial sensor to capture acceleration and angular velocity data during the control of a rat robot. Various machine learning algorithms, including Decision Trees, Random Forests, Logistic Regression, and Support Vector Machines, were employed to perform the classification of motion states. This detection system was tested in manual navigation experiments, with detection accuracy achieving 96.70%. The sequence of transient motion states could be further used as a promising reference for offline behaviour analysis.
3
Content available A feedback weighted fusion algorithm with dynamic sensor bias correction for gyroscope array
Yuan Ding, Qin Yongyuan, Shen Xiaowei, Wu Zongwei
Metrology and Measurement Systems
|
2021
|
Vol. 28, nr 1
161--179
EN
Low-cost Micro-Electromechanical System (MEMS) gyroscopes are known to have a smaller size, lower weight, and less power consumption than their more technologically advanced counterparts. However, current low-grade MEMS gyroscopes have poor performance and cannot compete with quality sensors in high accuracy navigational and guidance applications. The main focus of this paper is to investigate performance improvements by fusing multiple homogeneous MEMS gyroscopes. These gyros are transformed into a virtual gyro using a feedback weighted fusion algorithm with dynamic sensor bias correction. The gyroscope array combines eight homogeneous gyroscope units on each axis and divides them into two layers of differential configuration. The algorithm uses the gyroscope array estimation value to remove the gyroscope bias and then correct the gyroscope array measurement value. Then the gyroscope variance is recalculated in real time according to the revised measurement value and the weighted coefficients and state estimation of each gyroscope are deduced according to the least square principle. The simulations and experiments showed that the proposed algorithm could further reduce the drift and improve the overall accuracy beyond the performance limitations of individual gyroscopes. The maximum cumulative angle error was -2.09 degrees after 2000 seconds in the static test, and the standard deviation (STD) of the output fusion value of the proposed algorithm was 0.006 degrees/s in the dynamic test, which was only 1.7% of the STD value of an individual gyroscope.
4
Content available remote Chemotherapy-induced fatigue estimation using hidden Markov model
Ameli Sina, Naghdy Fazel, Stirling David, Naghdy Golshah, Aghmesheh Morteza
Biocybernetics and Biomedical Engineering
|
2019
|
Vol. 39, no. 1
176--187
EN
Chemotherapy-induced fatigue undermines the physical performance and alter gait behaviour of patients. In clinics, there is not a well-established method to objectively assess the effects of chemotherapy-induced fatigue on gait characteristics. Clinical trials commonly use 6 Minute Walking Tests (6MWT) to assess patients' gait. However, these studies only measure the distance that patients can walk. The distance does not provide comprehensive information about variations in ambulatory motion characteristics and body postural behaviour which can more appropriately describe the fatigue effects on general physical performance. Gait characteristics provide a manifestation of relationships between muscular and cardiovascular fitness status and physical motions. Hence, an assessment of gait characteristics provides more appropriate information about the effects of chemotherapy-induced fatigue on gait behaviour. A novel approach is proposed to objectively assess the impacts of chemotherapy-induced fatigue on cancer gait by analysing the gait characteristics during 6MWT. The joint angles of the lower body segments are measured by inertial sensors and modelled through a Hidden Markov Model (HMM) with Gaussian emissions. A Gaussian clustering method classifies the joint angles of first gait cycle to determine the six gait phases of a normal gait as initial training values. A comparison of gait characteristics before and after chemotherapy-induced fatigue determines the gait abnormalities. The method is applied to four cancer patients and outcomes are benchmarked against the gait of a healthy subject before and after running program-induced fatigue. The results indicate a more accurate quantitative-based tool to measure the effects of chemotherapy-induce fatigue on gait and physical performance.
5
Content available remote Analiza błędów losowych czujników bezwładnościowych przy pomocy metod wariancyjnych
Paszek J., Kaniewski P., Łabowski M.
Przegląd Elektrotechniczny
|
2016
|
R. 92, nr 1
62--67
PL
Artykuł porusza problem badania właściwości błędów losowych czujników inercjalnych. Wykorzystana w badaniach metoda wariancji Allana umożliwia określenie ich wartości na podstawie przebiegu czasowego sygnałów. Analizie poddano giroskopy i przyśpieszeniomierze dwóch czujników wykonanych w różnych technologiach. Na koniec opisano model propagacji błędów w dwuwymiarowym systemie nawigacji inercjalnej.
EN
This paper presents application of Allan Variance method for analysis of inertial sensors random errors. The research is based on data from two inertial sensors made in different technologies. Finally, the error propagation model of two-dimensional Inertial Navigation System is described.
6
Content available Pomiary kątów ugięcia kończyny w stawie z wykorzystaniem inercyjnego systemu Motion Capture
Kopniak P.
Pomiary Automatyka Kontrola
|
2014
|
R. 60, nr 8
590--593
PL
Artykuł dotyczy zastosowań systemu rejestracji ruchu wykorzystującego inercyjne czujniki MEMS do badań aparatu ruchu człowieka. Badania tego typu umożliwią dokładniejsze diagnozy ortopedyczne oraz weryfikację postępów rehabilitacji. W artykule opisano budowę, właściwości i zasadę działania systemu Xsens Xbus Kit opartego na czujnikach MTx, metody wyznaczania kąta ugięcia kończyny w stawie na podstawie danych otrzymywanych z czujników oraz przykładowe wyniki badań ruchliwości kończyny. W artykule zawarto także badania dokładności pomiaru kątów poprzez czujniki MTx.
EN
This paper concerns applications of a motion capture system based on MEMS inertial sensors to research of the human locomotion system. Such research will enable more accurate diagnosis and verification of progress of orthopedic rehabilitation. The aper describes the construction, properties and the principle of operation of the Xsens Xbus Kit based on MTx sensors (Fig. 1). It depicts the method of determining the angle of bend of the limb in a joint on the basis of data received from the sensors and sample results of the mobility of the limb, too. Each sensor of Xbus Kit system includes an integrated three-axis accelerometer, gyroscope and magnetometer. In addition, inside there is a signal processor that uses several profiles for the Kalman filter (Fig. 2). As a result, the sensors can return raw or processed data of acceleration or the Euler angles describing the orientation of the sensor in 3D space [7]. The research described in the paper deals with the measurement of the angle of band of the elbow. To measure the band of limb in the joint is sufficient to calculate the difference of yaw angles measured by two MTx sensors (Fig. 2). As a result of tests, the maximum error of the sensor measurement was determined. It was 1°. The sensors measured the angles accurately, consistently and done it in real time (Figs. 6 and 7). The performed studies also showed that the measurement deviations of MTx sensors did not depend on the position of the limb with the exception of the vertical orientation in which the X-axis sensor coincided with the direction of gravity. Then there is a mathematical singularity [7].
7
Content available Badanie czujników inercjalnych z wykorzystaniem metody analizy widmowej
Paszek J., Kaniewski P.
Pomiary Automatyka Kontrola
|
2014
|
R. 60, nr 9
702--704
PL
W artykule przedstawiono wyniki badań losowych zakłóceń pomiarów czujników inercjalnych z wykorzystaniem metody analizy widmowej. Do uzyskania wyników wykorzystano metodę analizy Gęstości Widmowej Mocy (GWM) sygnału z czujnika w celu wyznaczenia charakterystyk źródeł zakłóceń. Przedstawione zostały wyniki badań eksperymentalnych oraz ich porównanie z wynikami uzyskanymi metodą wariancji Allana (AV). Na koniec dokonano porównania wyników graficznej interpretacji krzywych GWM i AV analizowanych danych.
EN
The accuracy of Inertial Navigation Systems (INS) is limited by the performance of used inertial sensors. The measurement precision of gyroscopes and accelerometers is limited due to systematic and random errors. The systematic errors are deterministic and can be easily removed from measurements using mathematical modeling and calibration. The origin of the random errors is electronic noise which interferes in the full measurement spectrum. Thus, this error cannot be fully removed from the acquired data using filtering. Estimation of the random noise errors can be done using Power Spectral Density (PSD) or Allan Variance (AV) method [1, 2, 4, 6]. Both methods are used to decompose noise to its basic sources described by the power spectral model 1/fn [2, 3]. In this paper, the estimation of random noises using the PSD method is shown. The error model used for sensor analysis and the methodology of experiment are described. The spectral analysis of the random errors of the inertial sensors allows comparing the performance of the sensors made in different technologies i.e. microelectro-mechanical gyroscopes (MEMS) and fiber optic gyroscopes (FOG). The PSD and AV methods give information about noise sources which can be used to model and simulate the inertial sensors noise.
8
Content available Rozpoznawanie gestów z wykorzystaniem czujników inercyjnych o 9 stopniach swobody
Barczewska K., Drozd A., Folwarczny Ł.
Pomiary Automatyka Kontrola
|
2013
|
R. 59, nr 3
235--238
PL
Rozpoznawanie gestów za pomocą czujników inercyjnych może być alternatywą dla standardowych interfejsów człowiek-komputer. Do śledzenia gestów wykorzystano czujnik zawierający trójosiowy akcelerometr, magnetometr i żyroskop. W dotychczasowych badaniach bazowano na sygnałach przyspieszenia. Autorzy zaproponowali i porównali rozwiązania wykorzystujące zarówno analizę przyspieszenia, jak i orientacji w przestrzeni, a także umożliwili badanym osobom wykonywanie gestów w sposób naturalny. Wyniki pokazują, że za pomocą algorytmu DTW (Dynamic Time Warping) możliwa jest klasyfikacja indywidualna dla danej osoby (ze skutecznością 92%), a także klasyfikacja uogólniona - na podstawie uniwersalnego wzorca (ze skutecznością 83%).
EN
Gesture recognition may be applied to control of computer applica-tions and electronic devices as an alternative to standard human-machine interfaces. This paper reports a method of gesture classification based on analysis of data from 9DOF inertial sensor - NEC-TOKIN, Motion Sensor MDP-A3U9S (Fig.1). Nine volunteers were asked to perform 10 different gestures (shown in Fig.2) in a natural way with a sensor attached to their hand. The gesture data base consisting of 2160 files with triaxial acceleration and orientation signals was created. In the first step the data were divided into training and testing sets. The designed system uses the Dynamic Time Warping (DTW) algorithm to calculate similarity of signals (formulas (1)-(3)). Using this method the authors chose representative signals to indi-vidual and generalized exemplars data base from the training set. The DTW algorithm was also used in the classification process. Different recognition approaches were tested basing on acceleration-only, orientation-only and acceleration-orientation signals. The results listed in Tab.4 show that the best recognition efficiency of 92% was obtained in the individual recognition (only one person gestures taken into account) for modified exemplars data base. The modification proposed by the authors (Section 3) improved the recognition rate by 10 percentage points. The efficiency rate of 83% (Tab. 5) was reached in the generalized case. The next step of im-proving the designed recognition system is application of an inertial system with a bluetooth module and real-time gesture classification.
9
Content available Neck injury diagnostic device
Mielczarek A., Ritter R., Napieralski A.
International Journal of Microelectronics and Computer Science
|
2011
|
Vol. 2, nr 1
22-27
EN
The paper describes a method of automating a medical study of cervical spine condition with use of MEMS inertial sensors and a magnetometer. The examination procedure aims to detect and assess the dysfunction of the cervical spine. The same exercise may be also used for rehabilitation.
first rewind previous Strona / 1 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.