Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8993075
Durga Sundaram, Abhishek Sarode, K. George
This paper presents a trainable robotic arm with vision-based guidance capability. The arm can be trained to perform object manipulation tasks such as picking up an object from a location. The vision-based guidance, that utilizes a low-cost integrated webcam, augments the trainable arm's capability to pick up objects; it assists in situations in which the object to be manipulated is displaced from the location the arm was originally trained to pick up. The experimental results from 10 trails demonstrate the vision-based trainable arm's potential to be utilized as a robotic assistant for individuals with physical functioning difficulties.
{"title":"Vision-Based Trainable Robotic Arm for Individuals with Motor Disability","authors":"Durga Sundaram, Abhishek Sarode, K. George","doi":"10.1109/UEMCON47517.2019.8993075","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8993075","url":null,"abstract":"This paper presents a trainable robotic arm with vision-based guidance capability. The arm can be trained to perform object manipulation tasks such as picking up an object from a location. The vision-based guidance, that utilizes a low-cost integrated webcam, augments the trainable arm's capability to pick up objects; it assists in situations in which the object to be manipulated is displaced from the location the arm was originally trained to pick up. The experimental results from 10 trails demonstrate the vision-based trainable arm's potential to be utilized as a robotic assistant for individuals with physical functioning difficulties.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127146189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8993037
Lidong Wang, Randy Jones
Intrusion detection of computer networks is an important issue in cybersecurity. Networks generate stream data which are big data and often lead to challenges in intrusion detection. The ‘Variety’ and ‘Veracity’ characteristics of big data in network data are studied using $R$ and its functions in this paper. The statistics, correlation, and association of variables in the spam email database ‘spambase’ are analysed. The clustering analysis based on k-means and principal component analysis for the data dimension reduction of the database are performed. Spam-email intrusion is predicted based on the Naïve Bayesian classification and deep learning, respectively. The analytics of missing values and missing data patterns in a large data set of ‘VAST 2013’ (with multiple data types and a huge volume of missing values) is conducted and its missing data patterns are obtained.
{"title":"Big Data Analytics in Cybersecurity: Network Data and Intrusion Prediction","authors":"Lidong Wang, Randy Jones","doi":"10.1109/UEMCON47517.2019.8993037","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8993037","url":null,"abstract":"Intrusion detection of computer networks is an important issue in cybersecurity. Networks generate stream data which are big data and often lead to challenges in intrusion detection. The ‘Variety’ and ‘Veracity’ characteristics of big data in network data are studied using $R$ and its functions in this paper. The statistics, correlation, and association of variables in the spam email database ‘spambase’ are analysed. The clustering analysis based on k-means and principal component analysis for the data dimension reduction of the database are performed. Spam-email intrusion is predicted based on the Naïve Bayesian classification and deep learning, respectively. The analytics of missing values and missing data patterns in a large data set of ‘VAST 2013’ (with multiple data types and a huge volume of missing values) is conducted and its missing data patterns are obtained.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126138816","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8992977
William Shue, Nischal Paudyal, Mahmoud Rabiah, D. Dow, Mehmet Ergezer, Mira Yun
Diabetes can impair the circulation of blood in an individual suffering from said illness. Neuropathy, another medical complication of diabetes, inhibits the ability of a patient to sense pain and temperature changes, most often in their hands and feet. These medical complications together can be dangerous as an individual suffering from diabetes may be unable to detect a harmful change in the blood circulation of their feet. Undetected changes may lead to other medical issues such as calluses and foot ulcers. This study developed a prototype device for the insole of an individual's footwear that is capable of monitoring signs which gauge the health of a users feet. Based on the measured temperature of a users feet, a system issued alerts to indicate poor foot health. The insole system included a microcontroller, temperature and humidity sensors, a Bluetooth transceiver and an electrical heating pad. The Bluetooth module communicated with a smartphone application for event recording, alerts and communication with the user and other stakeholders. The prototype developed showed promise. However, further development and testing will be necessary toward deployment.
{"title":"A Thermally Regulated Footwear & Alerting System","authors":"William Shue, Nischal Paudyal, Mahmoud Rabiah, D. Dow, Mehmet Ergezer, Mira Yun","doi":"10.1109/UEMCON47517.2019.8992977","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8992977","url":null,"abstract":"Diabetes can impair the circulation of blood in an individual suffering from said illness. Neuropathy, another medical complication of diabetes, inhibits the ability of a patient to sense pain and temperature changes, most often in their hands and feet. These medical complications together can be dangerous as an individual suffering from diabetes may be unable to detect a harmful change in the blood circulation of their feet. Undetected changes may lead to other medical issues such as calluses and foot ulcers. This study developed a prototype device for the insole of an individual's footwear that is capable of monitoring signs which gauge the health of a users feet. Based on the measured temperature of a users feet, a system issued alerts to indicate poor foot health. The insole system included a microcontroller, temperature and humidity sensors, a Bluetooth transceiver and an electrical heating pad. The Bluetooth module communicated with a smartphone application for event recording, alerts and communication with the user and other stakeholders. The prototype developed showed promise. However, further development and testing will be necessary toward deployment.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123486513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8992973
A. Kim, Peter Kim
The 2020 US presidential election is still more than a year away, but the media is noisy due to the continuous registration of candidates that will face Trump in the election. Trump has already started to check is rivals through media. So far, Joe Biden and Bernie Sanders seem to have to most possibility to face Trump in the election. Sensitivity analysis was conducted to the data collected from Twitter from the year 2019. The positivity scores have been proved to effect approval ratings, they are estimated to effect the likeliness of becoming the most popular candidate. The data was compared to the past election from 2008, 2012, and 2016. The elections included the past rival background of Obama and McCain, Obama and Romney, Trump and Clinton to show how positive ratings effect the election. Tweets were collected through HTML and Python. The collected data was analyzed using SPSS and MS Excel. Data was defined into three major statuses; positive, negative, and neutral by a lexicon named Valence Aware Dictionary and Sediment Reasoner (VADER). The null hypothesis was rejected through Independent Sample T-Test, Mann-Whitney U Test, Kruskal Wallis Test to show the difference between means. Research results show who will become Trump's estimated competitor for the 2020 election.
{"title":"Estimation of the 2020 US Presidential Election Competition and Election Stratagies","authors":"A. Kim, Peter Kim","doi":"10.1109/UEMCON47517.2019.8992973","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8992973","url":null,"abstract":"The 2020 US presidential election is still more than a year away, but the media is noisy due to the continuous registration of candidates that will face Trump in the election. Trump has already started to check is rivals through media. So far, Joe Biden and Bernie Sanders seem to have to most possibility to face Trump in the election. Sensitivity analysis was conducted to the data collected from Twitter from the year 2019. The positivity scores have been proved to effect approval ratings, they are estimated to effect the likeliness of becoming the most popular candidate. The data was compared to the past election from 2008, 2012, and 2016. The elections included the past rival background of Obama and McCain, Obama and Romney, Trump and Clinton to show how positive ratings effect the election. Tweets were collected through HTML and Python. The collected data was analyzed using SPSS and MS Excel. Data was defined into three major statuses; positive, negative, and neutral by a lexicon named Valence Aware Dictionary and Sediment Reasoner (VADER). The null hypothesis was rejected through Independent Sample T-Test, Mann-Whitney U Test, Kruskal Wallis Test to show the difference between means. Research results show who will become Trump's estimated competitor for the 2020 election.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122480356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8992985
Xiao Sha, Yasha Karimi, Samir R Das, P. Djurić, M. Stanaćević
Distribution of a large number of mm-sized sensing units in brain is a vision for the next generation of implantable devices for neural recording. Recorded data from the implants is conventionally transferred to a central external device and the bandwidth of the uplink channel is limited by the number of the implanted units. For the first time, we demonstrate the feasibility of local communication between mm-sized coils using backscattering technique which promises to reduce the requirement on the uplink bandwidth between the external device and the implants. To demonstrate the feasibility of the proposed link, two implanted coils located at 14 mm implantation depth are used with the distance between coils of 1.5 mm. The transmitting coil switches between two terminating impedance and the input voltage at the receiving coil is observed in the simulations with a triple-loop inductive link designed at 90 MHz. We show that the voltage difference in the received signal for two transmitting states can be resolved by demodulator of the receiving implant demonstrating the link feasibility. Several simulations show the functionality of the link under wide range of different angular and lateral misalignment.
{"title":"Study of mm-sized Coil to Coil Backscatter Based Communication Link","authors":"Xiao Sha, Yasha Karimi, Samir R Das, P. Djurić, M. Stanaćević","doi":"10.1109/UEMCON47517.2019.8992985","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8992985","url":null,"abstract":"Distribution of a large number of mm-sized sensing units in brain is a vision for the next generation of implantable devices for neural recording. Recorded data from the implants is conventionally transferred to a central external device and the bandwidth of the uplink channel is limited by the number of the implanted units. For the first time, we demonstrate the feasibility of local communication between mm-sized coils using backscattering technique which promises to reduce the requirement on the uplink bandwidth between the external device and the implants. To demonstrate the feasibility of the proposed link, two implanted coils located at 14 mm implantation depth are used with the distance between coils of 1.5 mm. The transmitting coil switches between two terminating impedance and the input voltage at the receiving coil is observed in the simulations with a triple-loop inductive link designed at 90 MHz. We show that the voltage difference in the received signal for two transmitting states can be resolved by demodulator of the receiving implant demonstrating the link feasibility. Several simulations show the functionality of the link under wide range of different angular and lateral misalignment.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130462073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8993047
Md Reshad Ul Hoque, R. Burks, C. Kwan, Jiang Li
The aim of image super-Resolution (SR) is to enhance image resolution while still retain the integrity of the original image. There are many ongoing types of research on image super-resolution for natural images, but any a few on remote sensing images. In this paper, we proposed deep learning-based image super-resolution techniques, including convolutional neural network (CNN) and generative adversarial network (GAN) to enhance the resolution of remote sensing images by a factor 4. In CNN, it learns an end to end mapping from low-resolution image to high-resolution image whereas, in GAN, the model learns the mapping guided by the GAN loss and gives the sharper appearance in high-resolution images. Our experimental results show that visually GAN models perform well but are inferior to other models in terms of image quality metrics, whereas quantitatively CNN models outperform other super-resolution models.
{"title":"Deep Learning for Remote Sensing Image Super-Resolution","authors":"Md Reshad Ul Hoque, R. Burks, C. Kwan, Jiang Li","doi":"10.1109/UEMCON47517.2019.8993047","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8993047","url":null,"abstract":"The aim of image super-Resolution (SR) is to enhance image resolution while still retain the integrity of the original image. There are many ongoing types of research on image super-resolution for natural images, but any a few on remote sensing images. In this paper, we proposed deep learning-based image super-resolution techniques, including convolutional neural network (CNN) and generative adversarial network (GAN) to enhance the resolution of remote sensing images by a factor 4. In CNN, it learns an end to end mapping from low-resolution image to high-resolution image whereas, in GAN, the model learns the mapping guided by the GAN loss and gives the sharper appearance in high-resolution images. Our experimental results show that visually GAN models perform well but are inferior to other models in terms of image quality metrics, whereas quantitatively CNN models outperform other super-resolution models.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129995703","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8992979
S. Kuruppu, Alexander Shibilski
Digital controls have become the primary form of control in numerous applications due to the advancements in semiconductor industry and lower cost. Digital control algorithms implemented on digital signal processors (DSPs) or microcontrollers execute the algorithm at a specified clock frequency. Discrete time algorithms such as digital filters and digital PID controllers require the sampling period in the controller design, which is directly related to the microcontroller clock frequency. Due to aging, manufacturing process defects and environment conditions cause the clock frequency to drift from the specification. Such variation affects the discrete time algorithm performance deviate from expected performance.
{"title":"Clock Variation Impact on Digital Control System Performance","authors":"S. Kuruppu, Alexander Shibilski","doi":"10.1109/UEMCON47517.2019.8992979","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8992979","url":null,"abstract":"Digital controls have become the primary form of control in numerous applications due to the advancements in semiconductor industry and lower cost. Digital control algorithms implemented on digital signal processors (DSPs) or microcontrollers execute the algorithm at a specified clock frequency. Discrete time algorithms such as digital filters and digital PID controllers require the sampling period in the controller design, which is directly related to the microcontroller clock frequency. Due to aging, manufacturing process defects and environment conditions cause the clock frequency to drift from the specification. Such variation affects the discrete time algorithm performance deviate from expected performance.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131172234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8992968
A. F. R. Olaya, J. Antelis, A. Cerquera
It has been widely reported that patterns of EEG generated when a person performs a mental strategy can be recognized by signal processing algorithms. Among those mental strategies are the EEG-based brain-computer interface (BCI) paradigms. Furthermore, recognized patterns can be used as a source of information for communication to operate devices of BCI. Steady-State Visually Evoked Potentials (SSVEP) is a BCI paradigm that uses EEG brain responses when a subject focuses on a visual stimuli (flickering stimuli). Decoding SSVEP signals refers to identify what stimulus the user focuses on, which could be used as a command for communication or control. The minimum energy combination (MEC) and canonical correlation analysis methods (CCA) have been used in SSVEP-based BCIs due to its high efficiency, robustness, and simple implementation. In the last years, variants of CCA-based SSVEP methods have been reported in literature to improve classification and usability such as filter bank canonical correlation analysis (FBCCA). This paper evaluates the MEC, CCA and FBCCA methods for decoding commands from EEG signals in a SSVEP-based BCI application. It was carried out a set of experiments with five subjects which consist of four flickering stimuli (6.66, 7.5, 8.57 and 10 Hz) showed on a LED monitor. The results showed, for an epoch of 3 s, that CCA and FBCCA methods were able to detect SSVEP with high accuracy: 92.6% for FBCCA and 91.4% for CCA. The classification accuracy was 86.1% for MEC. As future work, FBCCA method will be used to decode user intention to control a closed-loop system based on EEG-triggered FES to restore hand grasp function.
{"title":"Decoding Steady-State Visual Evoked Potentials From EEG Signals: Towards an EEG-Triggered FES System to Restore Hand Grasp Function","authors":"A. F. R. Olaya, J. Antelis, A. Cerquera","doi":"10.1109/UEMCON47517.2019.8992968","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8992968","url":null,"abstract":"It has been widely reported that patterns of EEG generated when a person performs a mental strategy can be recognized by signal processing algorithms. Among those mental strategies are the EEG-based brain-computer interface (BCI) paradigms. Furthermore, recognized patterns can be used as a source of information for communication to operate devices of BCI. Steady-State Visually Evoked Potentials (SSVEP) is a BCI paradigm that uses EEG brain responses when a subject focuses on a visual stimuli (flickering stimuli). Decoding SSVEP signals refers to identify what stimulus the user focuses on, which could be used as a command for communication or control. The minimum energy combination (MEC) and canonical correlation analysis methods (CCA) have been used in SSVEP-based BCIs due to its high efficiency, robustness, and simple implementation. In the last years, variants of CCA-based SSVEP methods have been reported in literature to improve classification and usability such as filter bank canonical correlation analysis (FBCCA). This paper evaluates the MEC, CCA and FBCCA methods for decoding commands from EEG signals in a SSVEP-based BCI application. It was carried out a set of experiments with five subjects which consist of four flickering stimuli (6.66, 7.5, 8.57 and 10 Hz) showed on a LED monitor. The results showed, for an epoch of 3 s, that CCA and FBCCA methods were able to detect SSVEP with high accuracy: 92.6% for FBCCA and 91.4% for CCA. The classification accuracy was 86.1% for MEC. As future work, FBCCA method will be used to decode user intention to control a closed-loop system based on EEG-triggered FES to restore hand grasp function.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"103 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134192490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8992959
B. Abegaz
The dynamic stability of power systems consisting of multiple machines is affected by the excitation of each machine, the system configuration and the loading conditions. In this paper, a method that could improve the dynamic stability of power networks in the presence of internal and external disturbances is presented. Automatic voltage regulator (AVR) based clustering and dynamic excitation of machines is proposed. Distributed perturbations are used to evaluate the stability of an experimental New England 10-machine, 39-bus test system. From the results, it was seen that the proposed clustering-based excitation algorithm could uniquely improve the stability conditions of the perturbed New effectively power system by around 10%, which could not be achieved using other methods.
{"title":"Stability Improvement of Power Networks using Cluster based Dynamic Excitation of AVR","authors":"B. Abegaz","doi":"10.1109/UEMCON47517.2019.8992959","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8992959","url":null,"abstract":"The dynamic stability of power systems consisting of multiple machines is affected by the excitation of each machine, the system configuration and the loading conditions. In this paper, a method that could improve the dynamic stability of power networks in the presence of internal and external disturbances is presented. Automatic voltage regulator (AVR) based clustering and dynamic excitation of machines is proposed. Distributed perturbations are used to evaluate the stability of an experimental New England 10-machine, 39-bus test system. From the results, it was seen that the proposed clustering-based excitation algorithm could uniquely improve the stability conditions of the perturbed New effectively power system by around 10%, which could not be achieved using other methods.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130778564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/UEMCON47517.2019.8992988
Julia Knox, Eric M. Pereira, A. Sousa, D. Dow
The desire to live independently may conflict with safety and practical needs as old age progresses toward a state of frail elderly. With old age the risk of debilitating events rises. Having someone notice such a debilitating state and call for help becomes increasingly important. Thus, many elderly people move out of their independent residence and into a group setting, such as a nursing home, but with associated risk of depression, decline in self-confidence or self-determination. An activity monitoring system with sensors both on-body and in-home, which would detect possible debilitating events and send alerts for help, could allow some elderly people to maintain independent living. This project developed prototype modules to track room location, heart rate, and fall detection through sensors connected to a hub microcontroller system. A prototype system was developed and tested. The system shows promise but needs further development and testing before deployment.
{"title":"Activity Monitoring System to Support Elderly Independent Living","authors":"Julia Knox, Eric M. Pereira, A. Sousa, D. Dow","doi":"10.1109/UEMCON47517.2019.8992988","DOIUrl":"https://doi.org/10.1109/UEMCON47517.2019.8992988","url":null,"abstract":"The desire to live independently may conflict with safety and practical needs as old age progresses toward a state of frail elderly. With old age the risk of debilitating events rises. Having someone notice such a debilitating state and call for help becomes increasingly important. Thus, many elderly people move out of their independent residence and into a group setting, such as a nursing home, but with associated risk of depression, decline in self-confidence or self-determination. An activity monitoring system with sensors both on-body and in-home, which would detect possible debilitating events and send alerts for help, could allow some elderly people to maintain independent living. This project developed prototype modules to track room location, heart rate, and fall detection through sensors connected to a hub microcontroller system. A prototype system was developed and tested. The system shows promise but needs further development and testing before deployment.","PeriodicalId":187022,"journal":{"name":"2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130873500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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