Exploiting Performance of Different Low-Cost Sensors for Small Amplitude Oscillatory Motion Monitoring: Preliminary Comparisons in View of Possible Integration

We address the problem of low amplitude oscillatory motion detection through different low-cost sensors: a LIS3LV02DQ MEMS accelerometer, a Microsoft Kinect v2 range camera, and a uBlox 6 GPS receiver. Several tests were performed using a one-direction vibrating table with different oscillation frequencies (in the range 1.5–3 Hz) and small challenging amplitudes (0.02 m and 0.03 m). A Mikrotron EoSens high-resolution camera was used to give reference data. A dedicated software tool was developed to retrieve Kinect v2 results. The capabilities of the VADASE algorithm were employed to process uBlox 6 GPS receiver observations. In the investigated time interval (in the order of tens of seconds) the results obtained indicate that displacements were detected with the resolution of fractions of millimeters with MEMS accelerometer and Kinect v2 and few millimeters with uBlox 6. MEMS accelerometer displays the lowest noise but a significant bias, whereas Kinect v2 and uBlox 6 appear more stable. The results suggest the possibility of sensor integration both for indoor (MEMS accelerometer + Kinect v2) and for outdoor (MEMS accelerometer + uBlox 6) applications and seem promising for structural monitoring applications.

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Accuracy of a novel marker tracking approach based on the low-cost Microsoft Kinect v2 sensor

Medical Engineering & Physics ◽

10.1016/j.medengphy.2018.04.020 ◽

2018 ◽

Vol 59 ◽

pp. 63-69 ◽

Cited By ~ 10

Author(s):

Alessandro Timmi ◽

Gino Coates ◽

Karine Fortin ◽

David Ackland ◽

Adam L. Bryant ◽

...

Keyword(s):

Low Cost ◽

Microsoft Kinect ◽

Kinect V2 ◽

Marker Tracking

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HemoKinect: A Microsoft Kinect V2 Based Exergaming Software to Supervise Physical Exercise of Patients with Hemophilia

Sensors ◽

10.3390/s18082439 ◽

2018 ◽

Vol 18 (8) ◽

pp. 2439 ◽

Cited By ~ 11

Author(s):

Fernando Mateo ◽

Emilio Soria-Olivas ◽

Juan Carrasco ◽

Santiago Bonanad ◽

Felipe Querol ◽

...

Keyword(s):

Center Of Mass ◽

Software Tool ◽

Elbow Flexion ◽

Microsoft Kinect ◽

Difficulty Level ◽

Kinect V2 ◽

Remote Supervision ◽

Depth Sensors ◽

Body Tracking ◽

Flexion Extension

Patients with hemophilia need to strictly follow exercise routines to minimize their risk of suffering bleeding in joints, known as hemarthrosis. This paper introduces and validates a new exergaming software tool called HemoKinect that intends to keep track of exercises using Microsoft Kinect V2’s body tracking capabilities. The software has been developed in C++ and MATLAB. The Kinect SDK V2.0 libraries have been used to obtain 3D joint positions from the Kinect color and depth sensors. Performing angle calculations and center-of-mass (COM) estimations using these joint positions, HemoKinect can evaluate the following exercises: elbow flexion/extension, knee flexion/extension (squat), step climb (ankle exercise) and multi-directional balance based on COM. The software generates reports and progress graphs and is able to directly send the results to the physician via email. Exercises have been validated with 10 controls and eight patients. HemoKinect successfully registered elbow and knee exercises, while displaying real-time joint angle measurements. Additionally, steps were successfully counted in up to 78% of the cases. Regarding balance, differences were found in the scores according to the difficulty level and direction. HemoKinect supposes a significant leap forward in terms of exergaming applicability to rehabilitation of patients with hemophilia, allowing remote supervision.

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Assessing the Performance of RGB-D Sensors for 3D Fruit Crop Canopy Characterization under Different Operating and Lighting Conditions

Sensors ◽

10.3390/s20247072 ◽

2020 ◽

Vol 20 (24) ◽

pp. 7072

Author(s):

Jordi Gené-Mola ◽

Jordi Llorens ◽

Joan R. Rosell-Polo ◽

Eduard Gregorio ◽

Jaume Arnó ◽

...

Keyword(s):

Precision Agriculture ◽

Low Cost ◽

Full Range ◽

Apple Orchard ◽

Microsoft Kinect ◽

Ambient Conditions ◽

Kinect V2 ◽

Depth Cameras ◽

Sensor Performance ◽

Agricultural Community

The use of 3D sensors combined with appropriate data processing and analysis has provided tools to optimise agricultural management through the application of precision agriculture. The recent development of low-cost RGB-Depth cameras has presented an opportunity to introduce 3D sensors into the agricultural community. However, due to the sensitivity of these sensors to highly illuminated environments, it is necessary to know under which conditions RGB-D sensors are capable of operating. This work presents a methodology to evaluate the performance of RGB-D sensors under different lighting and distance conditions, considering both geometrical and spectral (colour and NIR) features. The methodology was applied to evaluate the performance of the Microsoft Kinect v2 sensor in an apple orchard. The results show that sensor resolution and precision decreased significantly under middle to high ambient illuminance (>2000 lx). However, this effect was minimised when measurements were conducted closer to the target. In contrast, illuminance levels below 50 lx affected the quality of colour data and may require the use of artificial lighting. The methodology was useful for characterizing sensor performance throughout the full range of ambient conditions in commercial orchards. Although Kinect v2 was originally developed for indoor conditions, it performed well under a range of outdoor conditions.

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Low-cost MEMS accelerometer network for rotating machine vibration diagnostics

IEEE Instrumentation & Measurement Magazine ◽

10.1109/mim.2020.9234762 ◽

2020 ◽

Vol 23 (7) ◽

pp. 25-33

Author(s):

Luciane Agnoletti dos Santos Pedotti ◽

Ricardo Mazza Zago ◽

Mateus Giesbrecht ◽

Fabiano Fruett

Keyword(s):

Low Cost ◽

Vibration Diagnostics ◽

Mems Accelerometer ◽

Machine Vibration ◽

Rotating Machine

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Exploring the Effect of Temporal Aggregation on SCADA Data for Wind Turbine Prognosis Using a Normality Model

Applied Sciences ◽

10.3390/app11146405 ◽

2021 ◽

Vol 11 (14) ◽

pp. 6405

Author(s):

Pere Marti-Puig ◽

Alejandro Bennásar-Sevillá ◽

Alejandro Blanco-M. ◽

Jordi Solé-Casals

Keyword(s):

Wind Turbine ◽

Low Cost ◽

Wind Farms ◽

Temporal Aggregation ◽

Time Interval ◽

Irreversible Loss ◽

Loss Of Information ◽

Statistical Measures ◽

Maximum Value ◽

Additional Equipment

Today, the use of SCADA data for predictive maintenance and forecasting of wind turbines in wind farms is gaining popularity due to the low cost of this solution compared to others that require the installation of additional equipment. SCADA data provides four statistical measures (mean, standard deviation, maximum value, and minimum value) of hundreds of wind turbine magnitudes, usually in a 5-min or 10-min interval. Several studies have analysed the loss of information associated with the reduction of information when using five minutes instead of four seconds as a sampling frequency, or when compressing a time series recorded at 5 min to 10 min, concluding that some, but not all, of these magnitudes are seriously affected. However, to our knowledge, there are no studies on increasing the time interval beyond 10 min to take these four statistical values, and how this aggregation affects prognosis models. Our work shows that, despite the irreversible loss of information that occurs in the first 5 min, increasing the time considered to take the four representative statistical values improves the performance of the predicted targets in normality models.

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Best position method for experimental data acquisition systems using low-cost GPS receiver

Proceeding of the 2011 IEEE International Conference on Space Science and Communication (IconSpace) ◽

10.1109/iconspace.2011.6015883 ◽

2011 ◽

Cited By ~ 3

Author(s):

I. Abba ◽

W. A. W. Z. Abidin ◽

A. K. Othman ◽

K. H. Ping ◽

M. Abdullah ◽

...

Keyword(s):

Experimental Data ◽

Data Acquisition ◽

Low Cost ◽

Gps Receiver ◽

Data Acquisition Systems

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A 3D Deep Learning Approach for Classification of Gait Abnormalities Using Microsoft Kinect V2 Sensor

2021 26th International Computer Conference, Computer Society of Iran (CSICC) ◽

10.1109/csicc52343.2021.9420611 ◽

2021 ◽

Author(s):

Milad Shoryabi ◽

Ali Foroutannia ◽

Alireza Rowhanimanesh

Keyword(s):

Deep Learning ◽

Microsoft Kinect ◽

Learning Approach ◽

Kinect V2 ◽

Gait Abnormalities

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DEVELOPMENT OF A MOTION CAPTURE SYSTEM USING KINECT

Jurnal Teknologi ◽

10.11113/jt.v76.5917 ◽

2015 ◽

Vol 76 (11) ◽

Author(s):

Katherina Bujang ◽

Ahmad Faiz Ahmad Nazri ◽

Ahmad Fidaudin Ahmad Azam ◽

Jamaluddin Mahmud

Keyword(s):

Motion Capture ◽

Low Cost ◽

Microsoft Kinect ◽

Motion Capture Data ◽

Motion Capture System ◽

Interface Motion ◽

Measurement Analysis ◽

Potential Alternative ◽

Repeatability And Reproducibility ◽

Data Tracking

Microsoft Kinect has been identified as a potential alternative tool in the field of motion capture due to its simplicity and low cost. To date, the application and potential of Microsoft Kinect has been vigorously explored especially for entertainment and gaming purposes. However, its motion capture capability in terms of repeatability and reproducibility is still not well addressed. Therefore, this study aims to explore and develop a motion capture system using Microsoft Kinect; focusing on developing the interface, motion capture protocol as well as measurement analysis. The work is divided into several stages which include installation (Microsoft Kinect and MATLAB); parameters and experimental setup, interface development; protocols development; motion capture; data tracking and measurement analysis. The results are promising, where the variances are found to be less than 1% for both repeatability and reproducibility analysis. This proves that the current study is significant and the gained knowledge could contribute

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