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DeePaGait: Motor Assessment of Parkinson's Disease Using a Multi-Layer 1D Convolutional Neural Network on Smartphone Gait Data

DeePaGait: Motor Assessment of Parkinson's Disease Using a M...

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2022 IEEE International Conference on Big Data, Big Data 2022

作者： Abujrida, Hamza Agu, Emmanuel Pahlavan, Kaveh Worcester Polytechnic Institute Department of Electrical and Computer Engineering WorcesterMA01609 United States

ISBN: (纸本)9781665480451

Nearly 1 million people in the USA and 10 million people worldwide are living with Parkinson's disease (PD) [1]. The progression of the disease can be inferred from the changes in the patients' gait to inform early intervention. Due to their near-ubiquitous ownership, smartphone sensing is a very effective, highly available way of assessing gait. Objectives: In this work, we explore the inference of PD gait, by analyzing the patient's walk data collected from a smartphone in the patients' homes, using Deep Learning (DL) methods. Specifically, we investigate DL models to classify the severity of the motor part of the UPDRS (MDS-UPDRS 2.10-2.13). Methodology: Using data from the mPower study [2], we selected 152 PD patients who recorded at least 3 walks before taking their medication. We extracted gait cycles from the accelerometer and gyroscope sensor records and fed them to DeePaGait;our DL multi-layer Conventional Neural Network (CNN). DeePaGait operates on 1Dimensional convolution filters to classify 30 seconds of walking data into one of five severity levels (Normal, Slight, Mild, Moderate, Severe). Results: Our DeePaGait DL network was able to Classify the PD Walking-Balance, Shaking/Tremor, and Freeze of Gait (FoG) symptoms, with an accuracy of: 99.1%,98.4%, and 98.2% respectively. Conclusion: Despite the challenges of working with a patient-labeled, crowdsourced dataset, we were able to demonstrate that gait classification based on smartphone sensor data is a viable approach to infer the severity of PD gait anomalies. © 2022 IEEE.

关键词： Smartphones

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A Miniaturized ISFET-Based Blood pH Sensing Device for Home Care Use

A Miniaturized ISFET-Based Blood pH Sensing Device for Home ...

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2022 IEEE MIT Undergraduate Research Technology Conference, URTC 2022

作者： Buckley, Evan Geyster, Joshua Larkin, Benjamin Guler, Ulkuhan Worcester Polytechnic Institute Department of Electrical and Computer Engineering WorcesterMA01609 United States

ISBN: (纸本)9781665473453

This article presents the design of a miniaturized, minimally-invasive blood pH sensing device for medical point-of-care applications. Blood pH is a vital marker for determining respiratory and metabolic health. Abnormal blood pH levels indicate that the body's natural buffer system is out of balance, which may imply serious health issues, such as kidney damage, pneumonia, or heart failure. This work utilizes an Ion Sensitive Field Effect Transistor (ISFET) to measure the pH of a liquid solution with a future focus on blood pH measurements. We designed a readout circuit to convert the changing threshold voltage of the ISFET, based on the solution's pH level, to a pH measurement displayed on the device's screen in real-Time. With its portable size and its ability to accurately measure with a minimal amount of solution, this device may be a more convenient alternative for home use when compared to the current state-of-The-Art blood pH measurement techniques. © 2022 IEEE.

关键词： Threshold voltage

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Performance Analysis of a Flexible HPTS-Based Carbon Dioxide Sensor for Transcutaneous Blood Gas Monitoring

Performance Analysis of a Flexible HPTS-Based Carbon Dioxide...

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2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Tufan, Tuna B. Golemi, Kleo Apinis, Evan Pano, Kosti Hetzler, Zach Wei, Qingshan Guler, Ulkuhan Worcester Polytechnic Institute Department of Electrical and Computer Engineering WorcesterMA United States North Carolina State University Department of Chemical and Biomolecular Engineering RaleighNC United States

ISBN: (纸本)9798350300260

Traditional transcutaneous carbon dioxide sensing methods often require frequent calibration and the replacement of measurement electrodes, often deployed in large devices. In our pursuit of developing an accurate and noninvasive method for transcutaneous carbon dioxide sensing, we have introduced the utilization of a carbon dioxide-sensitive flexible sensor patch consisted of 8-hydroxypyrene-1,3,6-trisulfonate. To assess its performance, we have designed custom circuitry and conducted various tests to evaluate the sensor's reactivity to changes in the partial pressure of carbon dioxide, as well as its response to external parameters, such as excitation intensity, measurement drift, humidity, and temperature. Through our testing, we implemented a ratiometric approach and discovered that the sensor exhibits a linear relationship between the luminescence ratio and changes in carbon dioxide partial pressure. Within the clinically relevant range, we successfully measured carbon dioxide partial pressure, showing a variation of less than 3.9% across different levels of excitation intensity. © 2023 IEEE.

关键词： HPTS-based Carbon Dioxide Sensor Noninvasive Blood Gas Measurement Physiological Monitoring Remote Monitoring Transcutaneous Carbon Dioxide Sensing Wearable Devices

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Creating a Framework for Non-Profit Impact Reporting

Creating a Framework for Non-Profit Impact Reporting

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Annual IEEE Systems Conference

作者： Parker Langa Mona Blake Sarah Fenton Michael Nixdorf Shamsnaz V. Bhada Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA Mechanical Engineering Worcester Polytechnic Institute Worcester MA Chemical Engineering Worcester Polytechnic Institute Worcester MA Theoretical Physics Worcester Polytechnic Institute Worcester MA

ISBN: (数字)9798331508180

ISBN: (纸本)9798331508197

Non-profit organizations are increasingly pressured to provide impact analysis highlighting their community influence to continue receiving financial support. Organizations with limited resources can struggle in areas such as data organization, visualization, and conflicting stakeholders' expertise and interest. The need to show evidence-based impact while struggling with resources is a balancing act of survival for many non-profits and a unique case of a Socio-Technical system. In our research, we attempt to tackle this Socio-Technical problem by creating a framework and building tools to alleviate this balancing act to allow non-profits to devote their resources to supporting their mission. We use a mixed methods approach through data collection and analysis to provide a cohesive overview of a charity's influence while requiring few resources. We apply this method to Historic Buildings & Places (HB&P), a non-profit organization in the UK that works to preserve built heritage to retain its cultural value and increase sustainable infrastructure. Using HB&P as a case study provides an understanding of practices used to complete this mixed methods approach. This paper describes the process for determining impact criteria and creating an accessible report as well as providing a set of terms and a procedure applicable to non-profits across many sectors. The findings include which graphics wider audiences easily understand—column graphs and maps—and which themes are currently sought after—diversity and sustainability. Given our interview pool focused on current and potential stakeholders, non-profits who focus on highlighting their diversity and sustainability work through accessible graphics have the potential to increase their financial support.

关键词： Sociotechnical systems Visualization Data analysis Buildings Software Stakeholders Sustainable development Interviews Heat maps Lenses

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A Miniaturized Transcutaneous Carbon Dioxide Monitor Based on Dual Lifetime Referencing

A Miniaturized Transcutaneous Carbon Dioxide Monitor Based o...

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2022 IEEE Biomedical Circuits and Systems Conference, BioCAS 2022

作者： Tufan, Tuna B. Guler, Ulkuhan Worcester Polytechnic Institute Electrical and Computer Engineering WorcesterMA01609 United States

ISBN: (数字)9781665469173

ISBN: (纸本)9781665469173

The ability to monitor blood gases, namely oxy-gen and carbon dioxide, in real-time is of critical importance to clinicians in diagnosing and treating respiratory disorders. Transcutaneous monitors measure the partial pressure of carbon dioxide diffused from the skin. These monitors are noninvasive and capable of continuously monitoring carbon dioxide. Conventional transcutaneous carbon dioxide monitors require a heating element and large calibration equipment for reliable measurements. We propose a miniaturized transcutaneous carbon dioxide monitor based on a luminescence sensing film and dual lifetime referencing technique to assess the partial pressure of carbon dioxide within the 0-75 mmHg range, covering the clinically relevant range for healthy humans, 35-45 mmHg. We measured the partial pressure of carbon dioxide with less than ~1.6% error in the given range without any post-processing and heating. © 2022 IEEE.

关键词： Carbon dioxide

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Graph Coordinates and Conventional Neural Networks - An Alternative for Graph Neural Networks

Graph Coordinates and Conventional Neural Networks - An Alte...

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2023 IEEE International Conference on Big Data, BigData 2023

作者： Qin, Zheyi Paffenroth, Randy Jayasumana, Anura P. Colorado State University Electrical and Computer Engineering Fort Collins United States Worcester Polytechnic Institute Department of Data Science Program WorcesterMA United States

ISBN: (纸本)9798350324457

Graph-based data present unique challenges and opportunities for machine learning. Graph Neural Networks (GNNs), and especially those algorithms that capture graph topology through message passing for neighborhood aggregation, have been a leading solution. However, these networks often require substantial computational resources and may not optimally leverage the information contained in the graph's topology, particularly for large-scale or complex *** propose Topology Coordinate Neural Network (TCNN) and Directional Virtual Coordinate Neural Network (DVCNN) as novel and efficient alternatives to message passing GNNs, that directly leverage the graph's topology, sidestepping the computational challenges presented by competing algorithms. Our proposed methods can be viewed as a reprise of classic techniques for graph embedding for neural network feature engineering, but they are novel in that our embedding techniques leverage ideas in Graph Coordinates (GC) that are lacking in current *** results, benchmarked against the Open Graph Benchmark Leaderboard, demonstrate that TCNN and DVCNN achieve competitive or superior performance to message passing GNNs. For similar levels of accuracy and ROC-AUC, TCNN and DVCNN need far fewer trainable parameters than contenders of the OGBN Leaderboard. The proposed TCNN architecture requires fewer parameters than any neural network method currently listed in the OGBN Leaderboard for both OGBN-Proteins and OGBN-Products datasets. Conversely, our methods achieve higher performance for a similar number of trainable parameters. These results hold across diverse datasets and edge features, underscoring the robustness and generalizability of our methods. By providing an efficient and effective alternative to message passing GNNs, our work expands the toolbox of techniques for graph-based machine learning. A significantly lower number of tunable parameters for a given evaluation metric makes TCNN and DVCNN especiall

关键词： graph analytics graph coordinate graph embedding green AI network embedding

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FDM Printing: A Fabrication Method for Fluidic Soft Circuits?

FDM Printing: A Fabrication Method for Fluidic Soft Circuits...

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IEEE International Conference on Soft Robotics (RoboSoft)

作者： Savita V. Kendre Lehong Wang Ethan Wilke Nicholas Pacheco Loris Fichera Markus P. Nemitz Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Computer Science Worcester Polytechnic Institute Worcester MA USA Department of Biomedical Engineering Worcester Polytechnic Institute Worcester MA USA Department of Mechanical and Materials Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

Existing fluidic soft logic gates for controlling soft robots typically depend on labor-intensive manual fabrication or costly printing methods. In our research, we utilize Fused Deposition Modeling to create fully 3D-printed fluidic logic gates, fabricating a valve from thermoplastic polyurethane. We investigate the 3D printing of tubing and introduce a novel extrusion nozzle for tubing production. Our approach significantly reduces the production time for soft fluidic valves from 27 hours using replica molding to 3 hours with FDM printing. We apply our 3D-printed valve to develop optimized XOR gates and D-latch circuits, presenting a rapid and cost-effective fabrication method for fluidic logic gates that aims to make fluidic circuitry more accessible to the soft robotics community.

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T-Scope: Side-channel Leakage Assessment with a Hardware-accelerated Online TVLA Test

T-Scope: Side-channel Leakage Assessment with a Hardware-acc...

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Midwest Symposium on Circuits and Systems (MWSCAS)

作者： Hao Wang Andrew Malnicof Patrick Schaumont Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350387179

ISBN: (纸本)9798350387186

Test vector leakage assessment (TVLA) is a generic and commonly-used approach to assessing a device's side-channel vulnerability based on measuring a large number power traces. However, the current use model of TVLA uses batch processing which separates trace acquisition from statistical analysis, making the method harder to use in online, continuous-monitoring scenarios. We propose T-scope, a TVLA optimized for online testing of real-time targets. We use a pipelined solution to efficiently store power traces in compact histogram structures, and then use FPGA-based hardware acceleration of Welch's t-test to compute the TVLA. By continuously updating the histograms with newly acquired power traces, T-scope visualizes real-time changes in the side-channel leakage characteristics of the target. Our FPGA-based hardware-accelerator, created using high-level synthesis, offers a 99.93X performance gain over a software-based solution. We present a hardware demonstrator of a real-time display of the TVLA assessment of a leaky implementation of the Advanced Encryption Standard.

关键词： Histograms Visualization Power measurement Statistical analysis Performance gain Real-time systems Vectors

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Vision-based FDM Printing for Fabricating Airtight Soft Actuators

Vision-based FDM Printing for Fabricating Airtight Soft Actu...

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IEEE International Conference on Soft Robotics (RoboSoft)

作者： Yijia Wu Zilin Dai Haotian Liu Lehong Wang Markus P. Nemitz Department of Robotics Engineering Worcester Polytechnic Institute Worcester MA USA Department of Computer Science Worcester Polytechnic Institute Worcester MA USA Department of Mechanical and Materials Engineering Worcester Polytechnic Institute Worcester MA USA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

Pneumatic soft robots are typically fabricated by molding, a manual fabrication process that requires skilled labor. Additive manufacturing has the potential to break this limitation and speed up the fabrication process but struggles with consistently producing high-quality prints. We propose a low-cost approach to improve the print quality of desktop fused deposition modeling by adding a webcam to the printer to monitor the printing process and detect and correct defects such as holes or gaps. We demonstrate that our approach improves the air-tightness of printed pneumatic actuators while reducing the need for fine-tuning printing parameters. Our approach presents a new option for robustly fabricating airtight, soft robotic actuators.

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A Wearable Prototype Measuring PtcCO2 and SpO2

A Wearable Prototype Measuring PtcCO2 and SpO2

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IEEE Biomedical Circuits and Systems (BIOCAS)

作者： Kleo Golemi Evan Apinis Isil Isiksalan Vladimir Vakhter Ulkuhan Guler Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA USA

ISBN: (数字)9798350354959

ISBN: (纸本)9798350354966

The proper functioning of the respiratory system is evaluated by monitoring the exchange of blood oxygen and carbon dioxide. While wearable devices for monitoring both blood oxygen and carbon dioxide are emerging, wearable carbon dioxide monitors remain relatively rare. This paper introduces a novel wearable prototype that integrates the measurement of transcutaneous carbon dioxide and peripheral blood oxygen saturation on a miniaturized custom-designed printed circuit board. The device employs a fluorescent sensing film consisting of two distinct luminophore types and utilizes the time-domain dual lifetime referencing technique to enhance measurement accuracy by mitigating the effects of confounding factors. Thorough testing on human subjects validated the prototype’s functionality, comparing its performance against commercial clinical devices. The prototype effectively tracked changes in transcutaneous carbon dioxide induced by hyperventilation, with a resolution as low as 1 mmHg. Additionally, blood oxygen saturation measurements were tested on human subjects to compare our prototypes’ performance to that of clinical devices. The results confirm the potential of the proposed novel wearable for prolonged use with minimal maintenance and underscore its significance in advancing wearable health monitoring technologies.

关键词： Performance evaluation Accuracy Prototypes Carbon dioxide Sensors Biomedical monitoring Wearable devices Time-domain analysis Monitoring Blood

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