scholarly journals A Physiological Sensor-Based Android Application Synchronized with a Driving Simulator for Driver Monitoring

Sensors ◽  
2019 ◽  
Vol 19 (2) ◽  
pp. 399 ◽  
Author(s):  
David González-Ortega ◽  
Francisco Díaz-Pernas ◽  
Mario Martínez-Zarzuela ◽  
Míriam Antón-Rodríguez
Keyword(s):  
Driving Simulator ◽  
Android Application ◽  
Game Engine ◽  
Vehicle Data ◽  
Driver Monitoring ◽  
Skin Response ◽  
Android App ◽  
Physiological Sensors ◽  
Electrocardiogram Ecg ◽  
Physiological Sensor

In this paper, we present an Android application to control and monitor the physiological sensors from the Shimmer platform and its synchronized working with a driving simulator. The Android app can monitor drivers and their parameters can be used to analyze the relation between their physiological states and driving performance. The app can configure, select, receive, process, represent graphically, and store the signals from electrocardiogram (ECG), electromyogram (EMG) and galvanic skin response (GSR) modules and accelerometers, a magnetometer and a gyroscope. The Android app is synchronized in two steps with a driving simulator that we previously developed using the Unity game engine to analyze driving security and efficiency. The Android app was tested with different sensors working simultaneously at various sampling rates and in different Android devices. We also tested the synchronized working of the driving simulator and the Android app with 25 people and analyzed the relation between data from the ECG, EMG, GSR, and gyroscope sensors and from the simulator. Among others, some significant correlations between a gyroscope-based feature calculated by the Android app and vehicle data and particular traffic offences were found. The Android app can be applied with minor adaptations to other different users such as patients with chronic diseases or athletes.

VREED

2021 ◽  
Vol 5 (4) ◽  
pp. 1-20
Author(s):  
Luma Tabbaa ◽  
Ryan Searle ◽  
Saber Mirzaee Bafti ◽  
Md Moinul Hossain ◽  
Jittrapol Intarasisrisawat ◽  
...  
Keyword(s):  
Virtual Environments ◽  
Affective Computing ◽  
Pilot Trial ◽  
Emotional Responses ◽  
Physiological Signals ◽  
Skin Response ◽  
Electrocardiogram Ecg ◽  
Learning Analysis ◽  
Computing Literature ◽  
Healthy Participants

The paper introduces a multimodal affective dataset named VREED (VR Eyes: Emotions Dataset) in which emotions were triggered using immersive 360° Video-Based Virtual Environments (360-VEs) delivered via Virtual Reality (VR) headset. Behavioural (eye tracking) and physiological signals (Electrocardiogram (ECG) and Galvanic Skin Response (GSR)) were captured, together with self-reported responses, from healthy participants (n=34) experiencing 360-VEs (n=12, 1--3 min each) selected through focus groups and a pilot trial. Statistical analysis confirmed the validity of the selected 360-VEs in eliciting the desired emotions. Preliminary machine learning analysis was carried out, demonstrating state-of-the-art performance reported in affective computing literature using non-immersive modalities. VREED is among the first multimodal VR datasets in emotion recognition using behavioural and physiological signals. VREED is made publicly available on Kaggle1. We hope that this contribution encourages other researchers to utilise VREED further to understand emotional responses in VR and ultimately enhance VR experiences design in applications where emotional elicitation plays a key role, i.e. healthcare, gaming, education, etc.

Design of Android Based Smart Car

2017 ◽  
Vol 8 (3) ◽  
pp. 648
Author(s):  
D. Wilfred Shiju
Keyword(s):  
Mobile App ◽  
Android Application ◽  
System Use ◽  
Android App

Android smart car is designed with safety in mind. A simple and sensitiveline, included steering wheels and new voice events, this is designed to reduceinterruption so you can stay focused on the highway.This car which can be controlling using an Android APP for smart phones.A car is regularly an electronic mechanic machine that is guide by computer and electronic controlling programming. The innovation of the Smart Car technology to developing based on remote connection using android application can control the car movements. This system use Bluetooth device controller to control the mobile App. This Bluetooth device interface with UART communication. The UART receive the command via the Bluetooth device.   This design is may helps to our rural citifies. This system is developing to help to self driving vehicles.

scholarly journals Impact of Physiological Signals Acquisition in the Emotional Support Provided in Learning Scenarios

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4520 ◽  
Author(s):  
Uria-Rivas ◽  
Rodriguez-Sanchez ◽  
Santos ◽  
Vaquero ◽  
Boticario
Keyword(s):  
Emotional Support ◽  
Ambient Intelligence ◽  
Affective Computing ◽  
Emotional State ◽  
Signal To Noise Ratio ◽  
Physiological Signals ◽  
Emotional States ◽  
Skin Response ◽  
Physiological Sensors ◽  
Rule Based Approach

Physiological sensors can be used to detect changes in the emotional state of users with affective computing. This has lately been applied in the educational domain, aimed to better support learners during the learning process. For this purpose, we have developed the AICARP (Ambient Intelligence Context-aware Affective Recommender Platform) infrastructure, which detects changes in the emotional state of the user and provides personalized multisensorial support to help manage the emotional state by taking advantage of ambient intelligence features. We have developed a third version of this infrastructure, AICARP.V3, which addresses several problems detected in the data acquisition stage of the second version, (i.e., intrusion of the pulse sensor, poor resolution and low signal to noise ratio in the galvanic skin response sensor and slow response time of the temperature sensor) and extends the capabilities to integrate new actuators. This improved incorporates a new acquisition platform (shield) called PhyAS (Physiological Acquisition Shield), which reduces the number of control units to only one, and supports both gathering physiological signals with better precision and delivering multisensory feedback with more flexibility, by means of new actuators that can be added/discarded on top of just that single shield. The improvements in the quality of the acquired signals allow better recognition of the emotional states. Thereof, AICARP.V3 gives a more accurate personalized emotional support to the user, based on a rule-based approach that triggers multisensorial feedback, if necessary. This represents progress in solving an open problem: develop systems that perform as effectively as a human expert in a complex task such as the recognition of emotional states.

scholarly journals A Wearable Electrocardiogram Telemonitoring System for Atrial Fibrillation Detection

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 606 ◽  
Author(s):  
Minggang Shao ◽  
Zhuhuang Zhou ◽  
Guangyu Bin ◽  
Yanping Bai ◽  
Shuicai Wu
Keyword(s):  
Atrial Fibrillation ◽  
Ecg Monitoring ◽  
Web Browser ◽  
Ecg Signals ◽  
Cloud Server ◽  
Android App ◽  
Electrocardiogram Ecg ◽  
The Web ◽  
Ecg Data

In this paper we proposed a wearable electrocardiogram (ECG) telemonitoring system for atrial fibrillation (AF) detection based on a smartphone and cloud computing. A wearable ECG patch was designed to collect ECG signals and send the signals to an Android smartphone via Bluetooth. An Android APP was developed to display the ECG waveforms in real time and transmit every 30 s ECG data to a remote cloud server. A machine learning (CatBoost)-based ECG classification method was proposed to detect AF in the cloud server. In case of detected AF, the cloud server pushed the ECG data and classification results to the web browser of a doctor. Finally, the Android APP displayed the doctor’s diagnosis for the ECG signals. Experimental results showed the proposed CatBoost classifier trained with 17 selected features achieved an overall F1 score of 0.92 on the test set (n = 7270). The proposed wearable ECG monitoring system may potentially be useful for long-term ECG telemonitoring for AF detection.

scholarly journals Wearables and the Quantified Self: Systematic Benchmarking of Physiological Sensors

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4448 ◽  
Author(s):  
Günther Sagl ◽  
Bernd Resch ◽  
Andreas Petutschnig ◽  
Kalliopi Kyriakou ◽  
Michael Liedlgruber ◽  
...  
Keyword(s):  
Heart Rate ◽  
Galvanic Skin Response ◽  
Low Cost ◽  
Wearable Sensors ◽  
Sensor Data ◽  
Quantified Self ◽  
High Quality ◽  
Laboratory Equipment ◽  
Skin Response ◽  
Physiological Sensors

Wearable sensors are increasingly used in research, as well as for personal and private purposes. A variety of scientific studies are based on physiological measurements from such rather low-cost wearables. That said, how accurate are such measurements compared to measurements from well-calibrated, high-quality laboratory equipment used in psychological and medical research? The answer to this question, undoubtedly impacts the reliability of a study’s results. In this paper, we demonstrate an approach to quantify the accuracy of low-cost wearables in comparison to high-quality laboratory sensors. We therefore developed a benchmark framework for physiological sensors that covers the entire workflow from sensor data acquisition to the computation and interpretation of diverse correlation and similarity metrics. We evaluated this framework based on a study with 18 participants. Each participant was equipped with one high-quality laboratory sensor and two wearables. These three sensors simultaneously measured the physiological parameters such as heart rate and galvanic skin response, while the participant was cycling on an ergometer following a predefined routine. The results of our benchmarking show that cardiovascular parameters (heart rate, inter-beat interval, heart rate variability) yield very high correlations and similarities. Measurement of galvanic skin response, which is a more delicate undertaking, resulted in lower, but still reasonable correlations and similarities. We conclude that the benchmarked wearables provide physiological measurements such as heart rate and inter-beat interval with an accuracy close to that of the professional high-end sensor, but the accuracy varies more for other parameters, such as galvanic skin response.

Retail Store Evoluvation Between Customer–Vendor Using Li-Fi Technology

2019 ◽  
Vol 16 (8) ◽  
pp. 3316-3318 ◽  
Author(s):  
S. Dhamodaran ◽  
Md. Afridi ◽  
M. Rahul ◽  
J. Refonaa ◽  
K. Ashok Kumar
Keyword(s):  
Spatial Data ◽  
Retail Store ◽  
Payment System ◽  
Customer Behavior ◽  
Android Application ◽  
International Conference ◽  
Mobile Channel ◽  
Information And Communication ◽  
Android App ◽  
Energy Information

Predominantly all the customers are smartphone users and they want shopping to be easier and seamless. However, the retail store experiences in India does not tap into the mobile channel of interaction when the customer is in the shop. The implementation is that make the shopping easier. Developing the application in the Android platform. In this application, we can make easy checkout and pay the shopping bills in any wallets (Dhamodarn, S., et al., 2016. Identification of User Poi in Spatial Data Using Android Application. International Conference on Computation of Power, Energy Information and Communication (ICCPEIC). IEEE. ISBN: 978-1-5090-0901-5). And capturing the customer behavior in the store. The user will add the Product and corresponding ID and its Cost is added in the Android App and finally, total Payment is made by the user via an android based Payment system. Details are transferred to the shop server. If the customer makes any mistake during the billing of products. The alarm will be raised in the trolley and in the bill counter.

scholarly journals PERANCANGAN APLIKASI MOBILE SISTEM INFORMASI “KIFORM” BERBASIS ANDROID UNTUK MENINGKATKAN EFEKTIFITAS PELAYANAN PUBLIK TERHADAP MASYARAKAT PADA KELURAHAN SUKASARI

2016 ◽  
Vol 2 (2) ◽  
pp. 226-235
Author(s):  
Endang Suryana ◽  
M. Devi Adiansyah ◽  
Imami Fatimatun
Keyword(s):  
Information Technology ◽  
Public Service ◽  
Public Services ◽  
Public Information ◽  
Android Application ◽  
The Public ◽  
Urban Village ◽  
Service Information ◽  
Android App ◽  
The Village

Sukasari Urban Village is one of the villages located in the district Rajeg Tangerang District, Banten. Currently, the development of information technology very rapidly to take advantage of the android application system as enhancing the effectiveness and flexibility of activities to get the information, in this case related to the public service. It is important to get public information faster in the village Sukasari. Observations on public service activities in the Village Sukasari are less effective if it is not included with public service information applications based on Android. With information still use the public services at the village office mading so is difficult to get information society wards. Also the location of the residence community and urban village office to be the cause. By design kiForm app (android app) as a form of use of information technology will facilitate the public to get information public services wherever they are.

scholarly journals Spatial Analysis of Moments of Stress Derived from Wearable Sensor Data

2019 ◽  
Vol 2 ◽  
pp. 1-8
Author(s):  
Kalliopi Kyriakou ◽  
Bernd Resch
Keyword(s):  
Spatial Analysis ◽  
Urban Areas ◽  
Hot Spot ◽  
Low Cost ◽  
Field Studies ◽  
Physiological Signals ◽  
Sensor Data ◽  
Skin Response ◽  
Density Analysis ◽  
Physiological Sensors

Abstract. Over the last years, we have witnessed an increasing interest in urban health research using physiological sensors. There is a rich repertoire of methods for stress detection using various physiological signals and algorithms. However, most of the studies focus mainly on the analysis of the physiological signals and disregard the spatial analysis of the extracted geo-located emotions. Methodologically, the use of hotspot maps created through point density analysis dominates in previous studies, but this method may lead to inaccurate or misleading detection of high-intensity stress clusters. This paper proposes a methodology for the spatial analysis of moments of stress (MOS). In a first step, MOS are identified through a rule-based algorithm analysing galvanic skin response and skin temperature measured by low-cost wearable physiological sensors. For the spatial analysis, we introduce a MOS ratio for the geo-located detected MOS. This ratio normalises the detected MOS in nearby areas over all the available records for the area. Then, the MOS ratio is fed into a hot spot analysis to identify hot and cold spots. To validate our methodology, we carried out two real-world field studies to evaluate the accuracy of our approach. We show that the proposed approach is able to identify spatial patterns in urban areas that correspond to self-reported stress.

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