Towards robust, unobtrusive sensing of respiration using ultra-wideband impulse radar for the care of people living with dementia

The unobtrusive monitoring of vital signals and behaviour can be used to gather intelligence to support the care of people living with dementia. This can provide insights into the persons wellbeing and the neurogenerative process, as well as enable them to continue to live safely at home, thereby improving their quality of life. Within this context, this study investigated the deployability of non-contact respiration rate (RR) measurement based on an Ultra-Wideband (UWB) radar System-on-Chip (SoC). An algorithm was developed to simultaneously and continuously extract the respiration signal, together with the confidence level of the respiration signal and the target position, without needing any prior calibration. The radar-measured RR results were compared to the RR results obtained from a ground truth measure based on the breathing sound, and the error rates were within 8% with a mean value of 2.4%. The target localisation results match to the radarto-chest distances with a mean error rate of 5.4%. The tested measurement range was up to 5m. The results suggest that the algorithm could perform sufficiently well in non-contact stationary respiration rate detection.

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Development of a Non-Invasive On-Chip Interconnect Health Sensing Method Based on Bit Error Rates

Sensors ◽

10.3390/s18103234 ◽

2018 ◽

Vol 18 (10) ◽

pp. 3234

Author(s):

Insun Shin ◽

Kyoungmin Koo ◽

Daeil Kwon

Keyword(s):

Error Rates ◽

In Situ Monitoring ◽

Service Development ◽

Gradual Transition ◽

System Operation ◽

Network Systems ◽

Non Invasive ◽

On Chip ◽

Fault Diagnosis And Prognosis ◽

Dc Resistance

Electronic products and systems are widely used in industrial network systems, control devices, and data acquisition devices across many industry sectors. Failures of such electronic systems might lead to unexpected downtime, loss of productivity, additional work for repairs, and delay in product and service development. Thus, developing an appropriate sensing technique is necessary, because it is the first step in system fault diagnosis and prognosis. Many sensing techniques often require external and additional sensing devices, which might disturb system operation and consequently increase operating costs. In this study, we present an on-chip health sensing method for non-destructive and non-invasive interconnect degradation detection. Bit error rate (BER), which represents data integrity during digital signal transmission, was selected to sense interconnect health without connecting external sensing devices. To verify the health sensing performance, corrosion tests were conducted with in situ monitoring of the BER and direct current (DC) resistance. The eye size, extracted from the BER measurement, showed the highest separation between the intact and failed interconnect, as well as a gradual transition, compared with abrupt changes in the DC resistance, during interconnect degradation. These experimental results demonstrate the potential of the proposed sensing method for on-chip interconnect health monitoring applications without disturbing system operation.

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Modeling chaos in on-chip ultra-wideband chaotic oscillator

2012 IEEE/MTT-S International Microwave Symposium Digest ◽

10.1109/mwsym.2012.6259678 ◽

2012 ◽

Author(s):

Myunghwan Park ◽

John C. Rodgers ◽

Daniel P. Lathrop

Keyword(s):

Ultra Wideband ◽

Chaotic Oscillator ◽

On Chip

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Internet of medical things – integrated, ultrasound-based respiration monitoring system for incubators

10.7190/shu-thesis-00415 ◽

2020 ◽

Author(s):

◽

Tareq Abdulqader

Keyword(s):

Real Time ◽

Respiration Rate ◽

Surface Measurement ◽

Time Interval ◽

Portable Devices ◽

Important Indicator ◽

The Us ◽

Respiratory Signal ◽

Central Apnoea ◽

Respiration Signal

The study's aim was to develop a non-contact, ultrasound (US) based respiration rate and respiratory signal monitor suitable for babies in incubators. Respiration rate indicates average number of breaths per minute and is higher in young children than adults. It is an important indicator of health deterioration in critically ill patients. The current incubators do not have an integrated respiration monitor due to complexities in its adaptation. Monitoring respiratory signal assists in diagnosing respiration rated problems such as central Apnoea that can affect infants. US sensors are suitable for integration into incubators as US is a harmless and cost-effective technology. US beam is focused on the chest or abdomen. Chest or abdomen movements, caused by respiration process, result in variations in their distance to the US transceiver located at a distance of about 0.5 m. These variations are recorded by measuring the time of flight from transmitting the signal and its reflection from the monitored surface. Measurement of this delay over a time interval enables a respiration signal to be produced from which respiration rate and pauses in breathing are determined. To assess the accuracy of the developed device, a platform with a moving surface was devised. The magnitude and frequency of its surface movement were accurately controlled by its signal generator. The US sensor was mounted above this surface at a distance of 0.5 m. This US signal was wirelessly transmitted to a microprocessor board to digitise. The recorded signal that simulated a respiratory signal was subsequently stored and displayed on a computer or an LCD screen. The results showed that US could be used to measure respiration rate accurately. To cater for possible movement of the infant in the incubator, four US sensors were adapted. These monitored the movements from different angles. An algorithm to interpret the output from the four US sensors was devised and evaluated. The algorithm interpreted which US sensor best detected the chest movements. An IoMT system was devised that incorporated NodeMcu to capture signals from the US sensor. The detected data were transmitted to the ThingSpeak channel and processed in real-time by ThingSpeak’s add-on Matlab© feature. The data were processed on the cloud and then the results were displayed in real-time on a computer screen. The respiration rate and respiration signal could be observed remotely on portable devices e.g. mobile phones and tablets. These features allow caretakers to have access to the data at any time and be alerted to respiratory complications. A method to interpret the recorded US signals to determine respiration patterns, e.g. intermittent pauses, were implemented by utilising Matlab© and ThingSpeak Server. The method successfully detected respiratory pauses by identifying lack of chest movements. The approach can be useful in diagnosing central apnoea. In central apnoea, respiratory pauses are accompanied by cessation of chest or abdominal movements. The devised system will require clinical trials and integration into an incubator by conforming to the medical devices directives. The study demonstrated the integration of IoMT-US for measuring respiration rate and respiratory signal. The US produced respiration rate readings compared well with the actual signal generator's settings of the platform that simulated chest movements.

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Recent Advances in ASIC Development for Enhanced Performance M-Sequence UWB Systems

Sensors ◽

10.3390/s20174812 ◽

2020 ◽

Vol 20 (17) ◽

pp. 4812 ◽

Cited By ~ 1

Author(s):

Pavol Galajda ◽

Martin Pecovsky ◽

Miroslav Sokol ◽

Martin Kmec ◽

Dusan Kocur

Keyword(s):

Integrated Circuit ◽

Short Range ◽

Functional System ◽

Ultra Wideband ◽

Radar Sensors ◽

Sensing Applications ◽

Radio Detection ◽

M Sequence ◽

Application Specific Integrated Circuit ◽

On Chip

Short-range ultra-wideband (UWB) radar sensors belong to very promising sensing techniques that have received vast attention recently. The M-sequence UWB sensing techniques for radio detection and ranging feature several advantages over the other short-range radars, inter alia superior integration capabilities. The prerequisite to investigate their capabilities in real scenarios is the existence of physically available hardware, i.e., particular functional system blocks. In this paper, we present three novel blocks of M-sequence UWB radars exploiting application-specific integrated circuit (ASIC) technology. These are the integrated 15th-order M-sequence radar transceiver on one chip, experimental active Electronic Communication Committee (ECC) bandpass filter, and miniature transmitting UWB antenna with an integrated amplifier. All these are custom designs intended for the enhancement of capabilities of an M-sequence-based system family for new UWB short-range sensing applications. The design approaches and verification of the manufactured prototypes by measurements of the realized circuits are presented in this paper. The fine balance on technology capabilities (Fc of roughly 120 GHz) and thoughtful design process of the proposed blocks is the first step toward remarkably minimized devices, e.g., as System on Chip designs, which apparently allow broadening the range of new applications.

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A Comparative Study of Methods for Measurement of Energy of Computing

Energies ◽

10.3390/en12112204 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2204 ◽

Cited By ~ 10

Author(s):

Muhammad Fahad ◽

Arsalan Shahid ◽

Ravi Reddy Manumachu ◽

Alexey Lastovetsky

Keyword(s):

Predictive Models ◽

Ground Truth ◽

System Level ◽

Average Error ◽

Level Energy ◽

Physical Measurements ◽

Wide Range ◽

External Power ◽

On Chip ◽

Multicore Cpus

Energy of computing is a serious environmental concern and mitigating it is an important technological challenge. Accurate measurement of energy consumption during an application execution is key to application-level energy minimization techniques. There are three popular approaches to providing it: (a) System-level physical measurements using external power meters; (b) Measurements using on-chip power sensors and (c) Energy predictive models. In this work, we present a comprehensive study comparing the accuracy of state-of-the-art on-chip power sensors and energy predictive models against system-level physical measurements using external power meters, which we consider to be the ground truth. We show that the average error of the dynamic energy profiles obtained using on-chip power sensors can be as high as 73% and the maximum reaches 300% for two scientific applications, matrix-matrix multiplication and 2D fast Fourier transform for a wide range of problem sizes. The applications are executed on three modern Intel multicore CPUs, two Nvidia GPUs and an Intel Xeon Phi accelerator. The average error of the energy predictive models employing performance monitoring counters (PMCs) as predictor variables can be as high as 32% and the maximum reaches 100% for a diverse set of seventeen benchmarks executed on two Intel multicore CPUs (one Haswell and the other Skylake). We also demonstrate that using inaccurate energy measurements provided by on-chip sensors for dynamic energy optimization can result in significant energy losses up to 84%. We show that, owing to the nature of the deviations of the energy measurements provided by on-chip sensors from the ground truth, calibration can not improve the accuracy of the on-chip sensors to an extent that can allow them to be used in optimization of applications for dynamic energy. Finally, we present the lessons learned, our recommendations for the use of on-chip sensors and energy predictive models and future directions.

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Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Sci ◽

10.3390/sci2010007 ◽

2020 ◽

Vol 2 (1) ◽

pp. 7 ◽

Cited By ~ 2

Author(s):

Mickaël Delamare ◽

Remi Boutteau ◽

Xavier Savatier ◽

Nicolas Iriart

Keyword(s):

Motion Capture ◽

Indoor Environment ◽

Indoor Localization ◽

Ground Truth ◽

Industrial Applications ◽

Ultra Wideband ◽

Complex Environments ◽

Experimental Protocol ◽

Localization Systems ◽

Do So

Many applications in the context of Industry 4.0 require precise localization. However, indoor localization remains an open problem, especially in complex environments such as industrial environments. In recent years, we have seen the emergence of Ultra WideBand (UWB) localization systems. The aim of this article is to evaluate the performance of a UWB system to estimate the position of a person moving in an indoor environment. To do so, we implemented an experimental protocol to evaluate the accuracy of the UWB system both statically and dynamically. The UWB system is compared to a ground truth obtained by a motion capture system with a millimetric accuracy.

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Static and Dynamic Evaluation of an UWB Localization System for Industrial Applications

Sci ◽

10.3390/sci1030062 ◽

2019 ◽

Vol 1 (3) ◽

pp. 62 ◽

Cited By ~ 2

Author(s):

Mickael Delamare ◽

Remi Boutteau ◽

Xavier Savatier ◽

Nicolas Iriart

Keyword(s):

Motion Capture ◽

Indoor Environment ◽

Indoor Localization ◽

Ground Truth ◽

Industrial Applications ◽

Ultra Wideband ◽

Complex Environments ◽

Experimental Protocol ◽

Localization Systems ◽

Do So

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The Accuracy of the Microsoft Kinect V2 Sensor for Human Gait Analysis. A Different Approach for Comparison with the Ground Truth

Sensors ◽

10.3390/s20164405 ◽

2020 ◽

Vol 20 (16) ◽

pp. 4405

Author(s):

Diego Guffanti ◽

Alberto Brunete ◽

Miguel Hernando ◽

Javier Rueda ◽

Enrique Navarro Cabello

Keyword(s):

Gait Analysis ◽

Ground Truth ◽

Potential Method ◽

Error Rates ◽

Microsoft Kinect ◽

Human Gait ◽

Kinect V2 ◽

Dynamic Time ◽

Human Gait Analysis ◽

Sensor Accuracy

Several studies have examined the accuracy of the Kinect V2 sensor during gait analysis. Usually the data retrieved by the Kinect V2 sensor are compared with the ground truth of certified systems using a Euclidean comparison. Due to the Kinect V2 sensor latency, the application of a uniform temporal alignment is not adequate to compare the signals. On that basis, the purpose of this study was to explore the abilities of the dynamic time warping (DTW) algorithm to compensate for sensor latency (3 samples or 90 ms) and develop a proper accuracy estimation. During the experimental stage, six iterations were performed using the a dual Kinect V2 system. The walking tests were developed at a self-selected speed. The sensor accuracy for Euclidean matching was consistent with that reported in previous studies. After latency compensation, the sensor accuracy demonstrated considerably lower error rates for all joints. This demonstrated that the accuracy was underestimated due to the use of inappropriate comparison techniques. On the contrary, DTW is a potential method that compensates for the sensor latency, and works sufficiently in comparison with certified systems.

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