Enhancing Speech Recorded from a Wearable Sensor Using a Collection of Autoencoders

2020 ◽  
pp. 383-397
Author(s):  
Astryd González-Salazar ◽  
Michelle Gutiérrez-Muñoz ◽  
Marvin Coto-Jiménez
Keyword(s):  
Wearable Sensor

Spatial-temporal variables for swimming coaches: A comparison study between video and TritonWear sensor

2021 ◽  
pp. 174795412110137
Author(s):  
Robin Pla ◽  
Thibaut Ledanois ◽  
Escobar David Simbana ◽  
Anaël Aubry ◽  
Benjamin Tranchard ◽  
...  
Keyword(s):  
Swimming Performance ◽  
Video Recording ◽  
Open Water ◽  
Percentage Error ◽  
Stroke Index ◽  
Wearable Sensor ◽  
Stroke Length ◽  
Video Recordings ◽  
Temporal Variables ◽  
Training Sets

The main aim of this study was to evaluate the validity and the reliability of a swimming sensor to assess swimming performance and spatial-temporal variables. Six international male open-water swimmers completed a protocol which consisted of two training sets: a 6×100m individual medley and a continuous 800 m set in freestyle. Swimmers were equipped with a wearable sensor, the TritonWear to collect automatically spatial-temporal variables: speed, lap time, stroke count (SC), stroke length (SL), stroke rate (SR), and stroke index (SI). Video recordings were added as a “gold-standard” and used to assess the validity and the reliability of the TritonWear sensor. The results show that the sensor provides accurate results in comparison with video recording measurements. A very high accuracy was observed for lap time with a mean absolute percentage error (MAPE) under 5% for each stroke (2.2, 3.2, 3.4, 4.1% for butterfly, backstroke, breaststroke and freestyle respectively) but high error ranges indicate a dependence on swimming technique. Stroke count accuracy was higher for symmetric strokes than for alternate strokes (MAPE: 0, 2.4, 7.1 & 4.9% for butterfly, breaststroke, backstroke & freestyle respectively). The other variables (SL, SR & SI) derived from the SC and the lap time also show good accuracy in all strokes. The wearable sensor provides an accurate real time feedback of spatial-temporal variables in six international open-water swimmers during classical training sets (at low to moderate intensities), which could be a useful tool for coaches, allowing them to monitor training load with no effort.

Investigation of e-textile dipole antenna performance based on embroidery parameters

2021 ◽  
pp. 004051752110134
Author(s):  
Daniel Agu ◽  
Rachel J Eike ◽  
Allyson Cliett ◽  
Dawn Michaelson ◽  
Rinn Cloud ◽  
...  
Keyword(s):  
Frequency Band ◽  
Impedance Matching ◽  
Dipole Antenna ◽  
Water Soluble ◽  
Wearable Sensor ◽  
Dipole Antennas ◽  
Antenna Performance ◽  
Large Production ◽  
Lower Transmission ◽  
The Ideal

E-textile antennas have the potential to be the premier on-body wearable sensor. Embroidery techniques, which can be applied to produce e-textile antennas, assist in large production volumes and fast production speeds. This paper focuses on the effects of three commonly used embroidery parameters, namely stitch type, conductive thread location, and stabilizer, on the performance of embroidered dipole antennas in order to determine the ideal embroidery combination for optimal antenna performance. Fifty-four dipole antenna samples were fabricated and measured at the industrial, scientific, and medical (ISM) frequency band of 2.45 GHz. The results of this study show that machine-embroidered antenna designs with satin stitches resonate at a lower frequency and exhibit a lower transmission gain compared with those made with contour stiches, and the conductive thread location in the bobbin location plus the use of a water-soluble stabilizer can help improve impedance matching.

scholarly journals Rehabilitation and Return to Sport Assessment after Anterior Cruciate Ligament Injury: Quantifying Joint Kinematics during Complex High-Speed Tasks through Wearable Sensors

Sensors ◽  
2021 ◽  
Vol 21 (7) ◽  
pp. 2331
Author(s):  
Stefano Di Paolo ◽  
Nicola Francesco Lopomo ◽  
Francesco Della Villa ◽  
Gabriele Paolini ◽  
Giulio Figari ◽  
...  
Keyword(s):  
Anterior Cruciate Ligament ◽  
Excellent Agreement ◽  
High Speed ◽  
Cruciate Ligament ◽  
Wearable Sensors ◽  
Return To Sport ◽  
Acl Injury ◽  
Wearable Sensor ◽  
Anterior Cruciate ◽  
Full Body

The aim of the present study was to quantify joint kinematics through a wearable sensor system in multidirectional high-speed complex movements used in a protocol for rehabilitation and return to sport assessment after Anterior Cruciate Ligament (ACL) injury, and to validate it against a gold standard optoelectronic marker-based system. Thirty-four healthy athletes were evaluated through a full-body wearable sensor (MTw Awinda, Xsens) and a marker-based optoelectronic (Vicon Nexus, Vicon) system during the execution of three tasks: drop jump, forward sprint, and 90° change of direction. Clinically relevant joint angles of lower limbs and trunk were compared through Pearson’s correlation coefficient (r), and the Coefficient of Multiple Correlation (CMC). An excellent agreement (r > 0.94, CMC > 0.96) was found for knee and hip sagittal plane kinematics in all the movements. A fair-to-excellent agreement was found for frontal (r 0.55–0.96, CMC 0.63–0.96) and transverse (r 0.45–0.84, CMC 0.59–0.90) plane kinematics. Movement complexity slightly affected the agreement between the systems. The system based on wearable sensors showed fair-to-excellent concurrent validity in the evaluation of the specific joint parameters commonly used in rehabilitation and return to sport assessment after ACL injury for complex movements. The ACL professionals could benefit from full-body wearable technology in the on-field rehabilitation of athletes.

scholarly journals Biosignal Compression Toolbox for Digital Biomarker Discovery

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 516
Author(s):  
Brinnae Bent ◽  
Baiying Lu ◽  
Juseong Kim ◽  
Jessilyn P. Dunn
Keyword(s):  
Wavelet Transform ◽  
Singular Value Decomposition ◽  
Data Compression ◽  
Biomarker Discovery ◽  
Singular Value ◽  
Sensor Data ◽  
Discrete Wavelet ◽  
Wearable Sensor ◽  
Huffman Encoding ◽  
Value Decomposition

A critical challenge to using longitudinal wearable sensor biosignal data for healthcare applications and digital biomarker development is the exacerbation of the healthcare “data deluge,” leading to new data storage and organization challenges and costs. Data aggregation, sampling rate minimization, and effective data compression are all methods for consolidating wearable sensor data to reduce data volumes. There has been limited research on appropriate, effective, and efficient data compression methods for biosignal data. Here, we examine the application of different data compression pipelines built using combinations of algorithmic- and encoding-based methods to biosignal data from wearable sensors and explore how these implementations affect data recoverability and storage footprint. Algorithmic methods tested include singular value decomposition, the discrete cosine transform, and the biorthogonal discrete wavelet transform. Encoding methods tested include run-length encoding and Huffman encoding. We apply these methods to common wearable sensor data, including electrocardiogram (ECG), photoplethysmography (PPG), accelerometry, electrodermal activity (EDA), and skin temperature measurements. Of the methods examined in this study and in line with the characteristics of the different data types, we recommend direct data compression with Huffman encoding for ECG, and PPG, singular value decomposition with Huffman encoding for EDA and accelerometry, and the biorthogonal discrete wavelet transform with Huffman encoding for skin temperature to maximize data recoverability after compression. We also report the best methods for maximizing the compression ratio. Finally, we develop and document open-source code and data for each compression method tested here, which can be accessed through the Digital Biomarker Discovery Pipeline as the “Biosignal Data Compression Toolbox,” an open-source, accessible software platform for compressing biosignal data.

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