scholarly journals Activity Tracking Using Ear-Level Accelerometers

2021 ◽  
Vol 3 ◽  
Author(s):  
Martin A. Skoglund ◽  
Giovanni Balzi ◽  
Emil Lindegaard Jensen ◽  
Tanveer A. Bhuiyan ◽  
Sergi Rotger-Griful
Keyword(s):  
Hearing Aids ◽  
Environmental Changes ◽  
Classification Tree ◽  
Consumer Electronics ◽  
Sensor Technology ◽  
Detection Accuracy ◽  
Activity Classification ◽  
Activity Tracking ◽  
Step Detection ◽  
Motion Activity

Introduction: By means of adding more sensor technology, modern hearing aids (HAs) strive to become better, more personalized, and self-adaptive devices that can handle environmental changes and cope with the day-to-day fitness of the users. The latest HA technology available in the market already combines sound analysis with motion activity classification based on accelerometers to adjust settings. While there is a lot of research in activity tracking using accelerometers in sports applications and consumer electronics, there is not yet much in hearing research.Objective: This study investigates the feasibility of activity tracking with ear-level accelerometers and how it compares to waist-mounted accelerometers, which is a more common measurement location.Method: The activity classification methods in this study are based on supervised learning. The experimental set up consisted of 21 subjects, equipped with two XSens MTw Awinda at ear-level and one at waist-level, performing nine different activities.Results: The highest accuracy on our experimental data as obtained with the combination of Bagging and Classification tree techniques. The total accuracy over all activities and users was 84% (ear-level), 90% (waist-level), and 91% (ear-level + waist-level). Most prominently, the classes, namely, standing, jogging, laying (on one side), laying (face-down), and walking all have an accuracy of above 90%. Furthermore, estimated ear-level step-detection accuracy was 95% in walking and 90% in jogging.Conclusion: It is demonstrated that several activities can be classified, using ear-level accelerometers, with an accuracy that is on par with waist-level. It is indicated that step-detection accuracy is comparable to a high-performance wrist device. These findings are encouraging for the development of activity applications in hearing healthcare.

A network of low-cost temperature sensors for real-time monitoring of combined sewer overflow

2021 ◽  
Author(s):  
Mathias Riechel ◽  
Oriol Gutierrez ◽  
Silvia Busquets ◽  
Neus Amela ◽  
Valentina Dimova ◽  
...  
Keyword(s):  
Real Time ◽  
Low Cost ◽  
Temperature Sensors ◽  
Sensor Technology ◽  
Detection Accuracy ◽  
Combined Sewer Overflow ◽  
Monitoring Equipment ◽  
Flow Monitoring ◽  
Combined Sewer ◽  
Sewer Overflow

<p>The H2020 innovation project digital-water.city (DWC) aims at boosting the integrated management of water systems in five major European cities – Berlin, Copenhagen, Milan, Paris and Sofia – by leveraging the potential of data and digital technologies. The goal is to quantify the benefits of a panel of 15 innovative digital solutions and achieve their long-term uptake and successful integration in the existing digital systems and governance processes. One of these promising technologies is a new generation of sensors for measuring combined sewer overflow occurrence, developed by ICRA and IoTsens.</p><p>Recent EU regulations have correctly identified CSOs as an important source of contamination and promote appropriate monitoring of all CSO structures in order to control and avoid the detrimental effects on receiving waters. Traditionally there has been a lack of reliable data on the occurrence of CSOs, with the main limitations being: i) the high number of CSO structures per municipality or catchment and ii) the high cost of the flow-monitoring equipment available on the market to measure CSO events. These two factors and the technical constraints of accessing and installing monitoring equipment in some CSO structures have delayed the implementation of extensive monitoring of CSOs. As a result, utilities lack information about the behaviour of the network and potential impacts on the local water bodies.</p><p>The new sensor technology developed by ICRA and IoTsens provides a simple yet robust method for CSO detection based on the deployment of a network of innovative low-cost temperature sensors. The technology reduces CAPEX and OPEX for CSO monitoring, compared to classical flow or water level measurements, and allows utilities to monitor their network extensively. The sensors are installed at the overflows crest and measure air temperature during dry-weather conditions and water temperature when the overflow crest is submerged in case of a CSO event. A CSO event and its duration can be detected by a shift in observed temperature, thanks to the temperature difference between the air and the water phase. Artificial intelligence algorithms further help to convert the continuous measurements into binary information on CSO occurrence. The sensors can quantify the CSO occurrence and duration and remotely provide real-time overflow information through LoRaWAN/2G communication protocols.</p><p>The solution is being deployed since October 2020 in the cities of Sofia, Bulgaria, and Berlin, Germany, with 10 offline sensors installed in each city to improve knowledge on CSO emissions. Further 36 (Sofia) and 9 (Berlin) online sensors will follow this winter. Besides its main goal of improving knowledge on CSO emissions, data in Sofia will also be used to identify suspected dry-weather overflows due to blockages. In Berlin, data will be used to improve the accuracy of an existing hydrodynamic sewer model for resilience analysis, flood forecasting and efficient investment in stormwater management measures. First results show a good detection accuracy of CSO events with the offline version of the technology. As measurements are ongoing and further sensors will be added, an enhanced set of results will be presented at the conference.</p><p>Visit us: https://www.digital-water.city/ </p><p>Follow us: Twitter (@digitalwater_eu); LinkedIn (digital-water.city)</p>

scholarly journals An Adaptive Dual-Window Step Detection Method for a Waist-Worn Inertial Navigation System

2015 ◽  
Vol 69 (3) ◽  
pp. 659-672 ◽  
Author(s):  
Yanshun Zhang ◽  
Yunqiang Xiong ◽  
Yixin Wang ◽  
Chunyu Li ◽  
Zhanqing Wang
Keyword(s):  
Detection Method ◽  
Detection Accuracy ◽  
Vertical Acceleration ◽  
Navigation Systems ◽  
Step Frequency ◽  
Step Detection ◽  
Pedestrian Navigation ◽  
Centre Of Gravity ◽  
Window Approach ◽  
Dual Window

In waist-worn pedestrian navigation systems, the periodic vertical acceleration peak signal at body centre of gravity is widely used for detecting steps. Due to vibration and waist shaking interference, accelerometer output signals contain false peaks and thus reduce step detection accuracy. This paper analyses the relationship between periodic acceleration at pedestrian centre of gravity and walking stance during walking. An adaptive dual-window step detection method is proposed based on this analysis. The peak signal is detected by a dual-window and the window length is adjusted according to the change in step frequency. The adaptive dual window approach is shown to successfully suppress the effects of vibration and waist shaking, thereby improving the step detection accuracy. The effectiveness of this method is demonstrated through step detection experiments and pedestrian navigation positioning experiments respectively. The step detection error rate was found to be less than 0·15% in repeated experiments consisting of 345 steps, while the longer (about 1·3 km) pedestrian navigation experiments demonstrated typical positioning error was around 0·67% of the distance travelled.

scholarly journals A new kind of locked circuit: the Quasi-Periodic Locked Loop (Q-PLL)

2020 ◽  
Author(s):  
Diego Luis Gonzalez ◽  
Lorenzo Grassi ◽  
Alberto Maurizi
Keyword(s):  
Hearing Aids ◽  
Speech Intelligibility ◽  
Stochastic Perturbation ◽  
Wide Band ◽  
Point Of View ◽  
Consumer Electronics ◽  
Frequency Locking ◽  
Complex Sound ◽  
Periodic Input ◽  
Wide Band Noise

A new nonlinear circuit with frequency locking capability in the case of a generic quasi-periodic input, is presented. Due to this capability the circuit is called a Quasi-Periodic Locked Loop (Q-PLL). The locked frequency is parametrically selected from among those prescribed by the theory of resonances in dynamical systems. In particular, the locked frequency forms a three-frequency resonance with the frequencies of the quasi-periodic input. The circuit is able to lock also in case of deterministic perturbation (harmonics of the input frequencies) and stochastic perturbation (wide-band noise). The circuit is closely related to the pitch perception of complex sound in humans and, as such, can be considered a bio-inspired technology. From the point of view of applications, it may be considered as an extension of the Phase Locked Loop (PLL) with the additional ability of locking simultaneously to more than one frequency. Due to the dynamical and structural robustness of the locked states, the Q-PLL represents a tangible advance for the development of specific applications, for example, in medicine (hearing aids, and cochlear implants), in robotics (artificial senses), and in industrial and consumer electronics (improvement of speech intelligibility, pitch-based processing, etc.).

scholarly journals A new kind of locked circuit: the Quasi-Periodic Locked Loop (Q-PLL)

2021 ◽  
Author(s):  
Diego Luis Gonzalez ◽  
Lorenzo Grassi ◽  
Alberto Maurizi
Keyword(s):  
Hearing Aids ◽  
Speech Intelligibility ◽  
Stochastic Perturbation ◽  
Wide Band ◽  
Point Of View ◽  
Consumer Electronics ◽  
Frequency Locking ◽  
Periodic Input ◽  
Frequency Components ◽  
Wide Band Noise

A new nonlinear circuit with frequency locking capability in the case of a generic quasi-periodic input, is presented. Due to this capability the circuit is called a Quasi-Periodic Locked Loop (Q-PLL). The locked frequency is parametrically selected from among those prescribed by the theory of resonances in dynamical systems. In particular, the locked frequency forms a three-frequency resonance with the frequencies of the quasi-periodic input. The circuit is able to lock also in case of deterministic perturbation (additional frequency components) and stochastic perturbation (wide-band noise). The circuit is closely related to the pitch perception of complex sound in humans and, as such, can be considered a bio-inspired device. From the point of view of applications, it may be considered as an extension of the Phase Locked Loop (PLL) with the additional ability of locking simultaneously to more than one frequency. Due to the dynamical and structural robustness of the locked states, the Q-PLL represents a tangible advance for the development of specific applications, for example, in medicine (hearing aids, and cochlear implants), in robotics (artificial senses), and in industrial and consumer electronics (improvement of speech intelligibility, pitch-based processing, etc.).<br>

A New Intelligent Color Scale Sensor

2012 ◽  
Vol 571 ◽  
pp. 661-664
Author(s):  
Yong Cai Yang ◽  
Quan Zhang ◽  
Ri Min Pan
Keyword(s):  
Control System ◽  
System Design ◽  
Lower Cost ◽  
Control Unit ◽  
Response Speed ◽  
Sensor Technology ◽  
Detection Accuracy ◽  
Color Scale ◽  
Important Trend ◽  
Micro Control Unit

The intelligentizing of sensor has been an important trend for sensor technology in recent years. In this paper, the new structure of the intelligent color scale sensor is presented; especially the software system design of intelligent color scale sensor based on the photoelectric measurement is given in detail. By using the control system based on Micro Control Unit (MCU), which takes full advantage of the resources on MCU, a new digital intelligent color scale sensor is successfully developed at a lower cost. Also, it has an ideal performance on the key index such as sensitivity, detection accuracy, response speed, reliability, operability and degrees of protection.

BSN-Based Activity Classification: A Low Complexity Windowing-&-Classification Approach

2012 ◽  
Vol 85 ◽  
pp. 53-58 ◽  
Author(s):  
Matteo Giuberti ◽  
Gianluigi Ferrari
Keyword(s):  
Sensor Networks ◽  
Low Complexity ◽  
The Body ◽  
Body Sensor Networks ◽  
Detection Accuracy ◽  
Activity Classification ◽  
First Case ◽  
Monitoring Applications ◽  
Healthcare Monitoring ◽  
The Time Domain

Wireless sensor networks (WSNs) are becoming more and more attractive because of their flexibility. In particular, WSNs are being applied to a user body in order to monitor and detect some activities of daily living (ADL) performed by the user (e.g., for medical purposes). This class of WSNs are typically denoted as body sensor networks (BSNs). In this paper, we discuss BSN-based human activity classification. In particular, the goal of our approach is to detect a sequence of activities, chosen from a limited set of fixed known activities, by observing the outputs generated by accelerometers and gyroscopes at the sensors placed over the body. In general, our framework is based on low-complexity windowing-&-classification. First, we consider the case of disjoint (in the time domain) activities; then, we extend our approach to encompass a scenario with consecutive non-disjoint activities. While in the first case windowing is separate from classification, in the second case windowing and classification need to be carried out jointly. The obtained results show a significant detection accuracy of the proposed method, making it suitable for healthcare monitoring applications.

scholarly journals Review of Capacitive Touchscreen Technologies: Overview, Research Trends, and Machine Learning Approaches

Sensors ◽  
2021 ◽  
Vol 21 (14) ◽  
pp. 4776
Author(s):  
Hyoungsik Nam ◽  
Ki-Hyuk Seol ◽  
Junhee Lee ◽  
Hyeonseong Cho ◽  
Sang Won Jung
Keyword(s):  
Machine Learning ◽  
Consumer Electronics ◽  
Optical Methods ◽  
Detection Accuracy ◽  
Learning Approaches ◽  
Accuracy Improvement ◽  
Tablet Pcs ◽  
Long Time ◽  
Intuitive Interfaces ◽  
User Friendly

Touchscreens have been studied and developed for a long time to provide user-friendly and intuitive interfaces on displays. This paper describes the touchscreen technologies in four categories of resistive, capacitive, acoustic wave, and optical methods. Then, it addresses the main studies of SNR improvement and stylus support on the capacitive touchscreens that have been widely adopted in most consumer electronics such as smartphones, tablet PCs, and notebook PCs. In addition, the machine learning approaches for capacitive touchscreens are explained in four applications of user identification/authentication, gesture detection, accuracy improvement, and input discrimination.

scholarly journals Implementation of an Online Auditory Attention Detection Model with Electroencephalography in a Dichotomous Listening Experiment

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 531
Author(s):  
Seung-Cheol Baek ◽  
Jae Ho Chung ◽  
Yoonseob Lim
Keyword(s):  
Hearing Aids ◽  
Real Life ◽  
Auditory Attention ◽  
Detection Accuracy ◽  
Neurofeedback Training ◽  
Neural Signals ◽  
Detection Model ◽  
Proposed Model ◽  
Online Implementation ◽  
Listening Experiment

Auditory attention detection (AAD) is the tracking of a sound source to which a listener is attending based on neural signals. Despite expectation for the applicability of AAD in real-life, most AAD research has been conducted on recorded electroencephalograms (EEGs), which is far from online implementation. In the present study, we attempted to propose an online AAD model and to implement it on a streaming EEG. The proposed model was devised by introducing a sliding window into the linear decoder model and was simulated using two datasets obtained from separate experiments to evaluate the feasibility. After simulation, the online model was constructed and evaluated based on the streaming EEG of an individual, acquired during a dichotomous listening experiment. Our model was able to detect the transient direction of a participant’s attention on the order of one second during the experiment and showed up to 70% average detection accuracy. We expect that the proposed online model could be applied to develop adaptive hearing aids or neurofeedback training for auditory attention and speech perception.

scholarly journals A Step towards Neuro-Steered Hearing Aids: Integrated Portable Setup for Time- Synchronized Acoustic Stimuli Presentation and EEG Recording

2021 ◽  
Vol 7 (2) ◽  
pp. 855-858
Author(s):  
Steffen Dasenbrock ◽  
Sarah Blum ◽  
Stefan Debener ◽  
Volker Hohmann ◽  
Hendrik Kayser
Keyword(s):  
Hearing Aids ◽  
Hearing Aid ◽  
Simultaneous Recording ◽  
Event Related Potential ◽  
Sensor Technology ◽  
Laboratory Research ◽  
Linear Discriminant ◽  
Auditory Oddball ◽  
Eeg Data ◽  
Research Platform

Abstract Aiming to provide a portable research platform to develop algorithms for neuro-steered hearing aids, a joint hearing aid - EEG measurement setup was implemented in this work. The setup combines the miniaturized electroencephalography sensor technology cEEGrid with a portable hearing aid research platform - the Portable Hearing Laboratory. The different components of the system are connected wirelessly, using the lab streaming layer framework for synchronization of audio and EEG data streams. Our setup was shown to be suitable for simultaneous recording of audio and EEG signals used in a pilot study (n=5) to perform an auditory Oddball experiment. The analysis showed that the setup can reliably capture typical event-related potential responses. Furthermore, linear discriminant analysis was successfully applied for single-trial classification of P300 responses. The study showed that time-synchronized audio and EEG data acquisition is possible with the Portable Hearing Laboratory research platform.

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