scholarly journals Monitoring Flexions and Torsions of the Trunk via Gyroscope-Calibrated Capacitive Elastomeric Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (20) ◽  
pp. 6706
Author(s):  
Gabriele Frediani ◽  
Federica Vannetti ◽  
Leonardo Bocchi ◽  
Giovanni Zonfrillo ◽  
Federico Carpi
Keyword(s):  
Root Mean Square Error ◽  
Motion Capture ◽  
Low Cost ◽  
Wearable Sensors ◽  
Cost Effective ◽  
Capacitive Sensors ◽  
Mean Square ◽  
Body Movements ◽  
Wireless System ◽  
Compliant Electrodes

Reliable, easy-to-use, and cost-effective wearable sensors are desirable for continuous measurements of flexions and torsions of the trunk, in order to assess risks and prevent injuries related to body movements in various contexts. Piezo-capacitive stretch sensors, made of dielectric elastomer membranes coated with compliant electrodes, have recently been described as a wearable, lightweight and low-cost technology to monitor body kinematics. An increase of their capacitance upon stretching can be used to sense angular movements. Here, we report on a wearable wireless system that, using two sensing stripes arranged on shoulder straps, can detect flexions and torsions of the trunk, following a simple and fast calibration with a conventional tri-axial gyroscope on board. The piezo-capacitive sensors avoid the errors that would be introduced by continuous sensing with a gyroscope, due to its typical drift. Relative to stereophotogrammetry (non-wearable standard system for motion capture), pure flexions and pure torsions could be detected by the piezo-capacitive sensors with a root mean square error of ~8° and ~12°, respectively, whilst for flexion and torsion components in compound movements, the error was ~13° and ~15°, respectively.

scholarly journals Wearable Detection of Trunk Flexions: Capacitive Elastomeric Sensors Compared to Inertial Sensors

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5453
Author(s):  
Gabriele Frediani ◽  
Leonardo Bocchi ◽  
Federica Vannetti ◽  
Giovanni Zonfrillo ◽  
Federico Carpi
Keyword(s):  
Continuous Monitoring ◽  
Inertial Sensors ◽  
Wearable Sensors ◽  
Cost Effective ◽  
Dielectric Elastomers ◽  
Capacitive Sensors ◽  
Wireless System ◽  
Alternative Technology ◽  
Human Kinematics ◽  
Effective Technology

Continuous monitoring of flexions of the trunk via wearable sensors could help various types of workers to reduce risks associated with incorrect postures and movements. Stretchable piezo-capacitive elastomeric sensors based on dielectric elastomers have recently been described as a wearable, lightweight and cost-effective technology to monitor human kinematics. Their stretching causes an increase of capacitance, which can be related to angular movements. Here, we describe a wearable wireless system to detect flexions of the trunk, based on such sensors. In particular, we present: (i) a comparison of different calibration strategies for the capacitive sensors, using either an accelerometer or a gyroscope as an inclinometer; (ii) a comparison of the capacitive sensors’ performance with those of the accelerometer and gyroscope; to that aim, the three types of sensors were evaluated relative to stereophotogrammetry. Compared to the gyroscope, the capacitive sensors showed a higher accuracy. Compared to the accelerometer, their performance was lower when used as quasi-static inclinometers but also higher in case of highly dynamic accelerations. This makes the capacitive sensors attractive as a complementary, rather than alternative, technology to inertial sensors.

scholarly journals Low Cost Automatic Reconstruction of Tree Structure by AdQSM with Terrestrial Close-Range Photogrammetry

Forests ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1020
Author(s):  
Yanqi Dong ◽  
Guangpeng Fan ◽  
Zhiwu Zhou ◽  
Jincheng Liu ◽  
Yongguo Wang ◽  
...  
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Low Cost ◽  
Reference Value ◽  
Tree Height ◽  
Point Clouds ◽  
Tree Structure ◽  
Mean Square ◽  
Tree Model

The quantitative structure model (QSM) contains the branch geometry and attributes of the tree. AdQSM is a new, accurate, and detailed tree QSM. In this paper, an automatic modeling method based on AdQSM is developed, and a low-cost technical scheme of tree structure modeling is provided, so that AdQSM can be freely used by more people. First, we used two digital cameras to collect two-dimensional (2D) photos of trees and generated three-dimensional (3D) point clouds of plot and segmented individual tree from the plot point clouds. Then a new QSM-AdQSM was used to construct tree model from point clouds of 44 trees. Finally, to verify the effectiveness of our method, the diameter at breast height (DBH), tree height, and trunk volume were derived from the reconstructed tree model. These parameters extracted from AdQSM were compared with the reference values from forest inventory. For the DBH, the relative bias (rBias), root mean square error (RMSE), and coefficient of variation of root mean square error (rRMSE) were 4.26%, 1.93 cm, and 6.60%. For the tree height, the rBias, RMSE, and rRMSE were—10.86%, 1.67 m, and 12.34%. The determination coefficient (R2) of DBH and tree height estimated by AdQSM and the reference value were 0.94 and 0.86. We used the trunk volume calculated by the allometric equation as a reference value to test the accuracy of AdQSM. The trunk volume was estimated based on AdQSM, and its bias was 0.07066 m3, rBias was 18.73%, RMSE was 0.12369 m3, rRMSE was 32.78%. To better evaluate the accuracy of QSM’s reconstruction of the trunk volume, we compared AdQSM and TreeQSM in the same dataset. The bias of the trunk volume estimated based on TreeQSM was −0.05071 m3, and the rBias was −13.44%, RMSE was 0.13267 m3, rRMSE was 35.16%. At 95% confidence interval level, the concordance correlation coefficient (CCC = 0.77) of the agreement between the estimated tree trunk volume of AdQSM and the reference value was greater than that of TreeQSM (CCC = 0.60). The significance of this research is as follows: (1) The automatic modeling method based on AdQSM is developed, which expands the application scope of AdQSM; (2) provide low-cost photogrammetric point cloud as the input data of AdQSM; (3) explore the potential of AdQSM to reconstruct forest terrestrial photogrammetric point clouds.

Evaluation of a Low-Cost Pneumatic Plantar Pressure Insole for Predicting Ground Contact Kinetics

2016 ◽  
Vol 32 (2) ◽  
pp. 215-220 ◽  
Author(s):  
Daniel A. Jacobs ◽  
Daniel P. Ferris
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Plantar Pressure ◽  
Center Of Pressure ◽  
Low Cost ◽  
Position Vector ◽  
Mean Square ◽  
Torque Vector ◽  
Sit To Stand

Instrumented insoles could benefit locomotion research on healthy and clinical populations by providing data in natural settings outside of the laboratory. We designed a low-cost, instrumented insole with 8 pneumatic bladders to measure localized plantar pressure information. We collected gait data during treadmill walking at 1.0 m/s and 1.5 m/s and for sit-to-stand and stand-tosit tasks for 10 subjects. We estimated a common representation of ground kinetics (3-component force vector, 2-component center of pressure position vector, and a single-component torque vector) from the insole data. We trained an intertask neural network for each component of the kinetic data. For the walking tasks at 1.0 m/s and 1.5 m/s, the normalized root mean square error was between 3.1% and 12.9% and for the sit-to-stand and stand-to-sit tasks, the normalized root mean square error was between 3.3% and 21.3% Our findings suggest that the proposed low-cost, instrumented insoles could provide useful data about movement kinetics during real-world activities.

A Low-Cost Instrumented Spatial Linkage Accurately Determines ASIS Position during Cycle Ergometry

2007 ◽  
Vol 23 (3) ◽  
pp. 224-229 ◽  
Author(s):  
James C. Martin ◽  
Steven J. Elmer ◽  
Robert D. Horscroft ◽  
Nicholas A.T. Brown ◽  
Barry B. Shultz
Keyword(s):  
Motion Capture ◽  
Low Cost ◽  
Cost Effective ◽  
Cycle Ergometry ◽  
Two Dimensional ◽  
Motion Capture System ◽  
Valid Measure ◽  
Kinematic Data ◽  
Vertical Error ◽  
Parasagittal Plane

The purpose of this study was to develop and evaluate an alternative method for determining the position of the anterior superior iliac spine (ASIS) during cycling. The approach used in this study employed an instrumented spatial linkage (ISL) system to determine the position of the ASIS in the parasagittal plane. A two-segment ISL constructed using aluminum segments, bearings, and digital encoders was tested statically against a calibration plate and dynamically against a video-based motion capture system. Four well-trained cyclists provided data at three pedaling rates. Statically, the ISL had a mean horizontal error of 0.03 ± 0.21 mm and a mean vertical error of −0.13 ± 0.59 mm. Compared with the video-based motion capture system, the agreement of the location of the ASIS had a mean error of 0.30 ± 0.55 mm for the horizontal dimension and −0.27 ± 0.60 mm for the vertical dimension. The ISL system is a cost-effective, accurate, and valid measure for two-dimensional kinematic data within a range of motion typical for cycling.

scholarly journals Evaluation methods for low-cost particulate matter sensors

2021 ◽  
Author(s):  
Jeffrey K. Bean
Keyword(s):  
Quality Assurance ◽  
Particulate Matter ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Prediction Interval ◽  
Low Cost ◽  
Sensor Data ◽  
Rural Site ◽  
Mean Square

Abstract. Understanding and improving the quality of data generated from low-cost sensors is a crucial step in using these sensors to fill gaps in air quality measurement and understanding. This paper shows results from a 10-month long campaign that included side-by-side measurements and comparison between EPA-approved reference instruments and low-cost particulate matter sensors in Bartlesville, Oklahoma. At this rural site in the Midwestern United States the instruments typically encountered only low (under 20 µg/m3) concentrations of particulate matter, however higher concentrations (50–400 µg/m3) were observed on three different days during what were likely agricultural burning events. This study focused on methods for understanding and improving data quality for low-cost particulate matter sensors. The data offered insights on how averaging time, choice of reference instrument, and the observation of higher pollutant concentrations can all impact performance indicators (R2 and root mean square error) for an evaluation. The influence of these factors should be considered when comparing one sensor to another or when determining whether a sensor can produce data that fits a specific need. Though R2 and root mean square error remain the dominant metrics in sensor evaluations, an alternative approach using a prediction interval may offer more consistency between evaluations and a more direct interpretation of sensor data following an evaluation. Ongoing quality assurance for sensor data is needed to ensure data continues to meet expectations. Observations of trends in linear regression parameters and sensor bias were used to analyze calibration and other quality assurance techniques.

scholarly journals Evaluation methods for low-cost particulate matter sensors

2021 ◽  
Vol 14 (11) ◽  
pp. 7369-7379
Author(s):  
Jeffrey K. Bean
Keyword(s):  
United States ◽  
Quality Assurance ◽  
Particulate Matter ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Low Cost ◽  
Sensor Data ◽  
Rural Site ◽  
Mean Square

Abstract. Understanding and improving the quality of data generated from low-cost sensors represent a crucial step in using these sensors to fill gaps in air quality measurement and understanding. This paper shows results from a 10-month-long campaign that included side-by-side measurements and comparison between reference instruments approved by the United States Environmental Protection Agency (EPA) and low-cost particulate matter sensors in Bartlesville, Oklahoma. At this rural site in the Midwestern United States the instruments typically encountered only low (under 20 µg m−3) concentrations of particulate matter; however, higher concentrations (50–400 µg m−3) were observed on 3 different days during what were likely agricultural burning events. This study focused on methods for understanding and improving data quality for low-cost particulate matter sensors. The data offered insights on how averaging time, choice of reference instrument, and the observation of higher pollutant concentrations can all impact performance indicators (R2 and root mean square error) for an evaluation. The influence of these factors should be considered when comparing one sensor to another or when determining whether a sensor can produce data that fit a specific need. Though R2 and root mean square error remain the dominant metrics in sensor evaluations, an alternative approach using a prediction interval may offer more consistency between evaluations and a more direct interpretation of sensor data following an evaluation. Ongoing quality assurance for sensor data is needed to ensure that data continue to meet expectations. Observations of trends in linear regression parameters and sensor bias were used to analyze calibration and other quality assurance techniques.

scholarly journals Mapping Topobathymetry in a Shallow Tidal Environment Using Low-Cost Technology

2020 ◽  
Vol 12 (9) ◽  
pp. 1394 ◽  
Author(s):  
Sibila A. Genchi ◽  
Alejandro J. Vitale ◽  
Gerardo M. E. Perillo ◽  
Carina Seitz ◽  
Claudio A. Delrieux
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Root Mean Square ◽  
Low Cost ◽  
Vertical Plane ◽  
Detailed Knowledge ◽  
Mean Square ◽  
Bahía Blanca Estuary ◽  
Weighting Method ◽  
Data Source

Detailed knowledge of nearshore topography and bathymetry is required for a wide variety of purposes, including ecosystem protection, coastal management, and flood and erosion monitoring and research, among others. Both topography and bathymetry are usually studied separately; however, many scientific questions and challenges require an integrated approach. LiDAR technology is often the preferred data source for the generation of topobathymetric models, but because of its high cost, it is necessary to exploit other data sources. In this regard, the main goal of this study was to present a methodological proposal to generate a topobathymetric model, using low-cost unmanned platforms (unmanned aerial vehicle and unmanned surface vessel) in a very shallow/shallow and turbid tidal environment (Bahía Blanca estuary, Argentina). Moreover, a cross-analysis of the topobathymetric and the tide level data was conducted, to provide a classification of hydrogeomorphic zones. As a main result, a continuous terrain model was built, with a spatial resolution of approximately 0.08 m (topography) and 0.50 m (bathymetry). Concerning the structure from motion-derived topography, the accuracy gave a root mean square error of 0.09 m for the vertical plane. The best interpolated bathymetry (inverse distance weighting method), which was aligned to the topography (as reference), showed a root mean square error of 0.18 m (in average) and a mean absolute error of 0.05 m. The final topobathymetric model showed an adequate representation of the terrain, making it well suited for examining many landforms. This study helps to confirm the potential for remote sensing of shallow tidal environments by demonstrating how the data source heterogeneity can be exploited.

scholarly journals A Novel Sensorised Insole for Sensing Feet Pressure Distributions

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 747 ◽  
Author(s):  
Ines Sorrentino ◽  
Francisco Javier Andrade Chavez ◽  
Claudia Latella ◽  
Luca Fiorio ◽  
Silvio Traversaro ◽  
...  
Keyword(s):  
Vacuum Chamber ◽  
Wearable Sensors ◽  
Ground Truth ◽  
Cost Effective ◽  
Contact Forces ◽  
Mean Square ◽  
Centre Of Pressure ◽  
Contact Pressure Distribution ◽  
Calibration Technique ◽  
Pressure Distributions

Wearable sensors are gaining in popularity because they enable outdoor experimental monitoring. This paper presents a cost-effective sensorised insole based on a mesh of tactile capacitive sensors. Each sensor’s spatial resolution is about 4 taxels/cm 2 in order to have an accurate reconstruction of the contact pressure distribution. As a consequence, the insole provides information such as contact forces, moments, and centre of pressure. To retrieve this information, a calibration technique that fuses measurements from a vacuum chamber and shoes equipped with force/torque sensors is proposed. The validation analysis shows that the best performance achieved a root mean square error (RMSE) of about 7   N for the contact forces and 2   N m for the contact moments when using the force/torque shoe data as ground truth. Thus, the insole may be an alternative to force/torque sensors for certain applications, with a considerably more cost-effective and less invasive hardware.

scholarly journals An Integrated Multi-Sensor Approach for the Remote Monitoring of Parkinson’s Disease

Sensors ◽  
2019 ◽  
Vol 19 (21) ◽  
pp. 4764 ◽  
Author(s):  
Giovanni Albani ◽  
Claudia Ferraris ◽  
Roberto Nerino ◽  
Antonio Chimienti ◽  
Giuseppe Pettiti ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Remote Monitoring ◽  
Rating Scale ◽  
Population Aging ◽  
Neurological Diseases ◽  
Low Cost ◽  
Wearable Sensors ◽  
Cost Effective ◽  
The Body

The increment of the prevalence of neurological diseases due to the trend in population aging demands for new strategies in disease management. In Parkinson’s disease (PD), these strategies should aim at improving diagnosis accuracy and frequency of the clinical follow-up by means of decentralized cost-effective solutions. In this context, a system suitable for the remote monitoring of PD subjects is presented. It consists of the integration of two approaches investigated in our previous works, each one appropriate for the movement analysis of specific parts of the body: low-cost optical devices for the upper limbs and wearable sensors for the lower ones. The system performs the automated assessments of six motor tasks of the unified Parkinson’s disease rating scale, and it is equipped with a gesture-based human machine interface designed to facilitate the user interaction and the system management. The usability of the system has been evaluated by means of standard questionnaires, and the accuracy of the automated assessment has been verified experimentally. The results demonstrate that the proposed solution represents a substantial improvement in PD assessment respect to the former two approaches treated separately, and a new example of an accurate, feasible and cost-effective mean for the decentralized management of PD.

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