Generated from prompt:
پرزنتیشن درباره دستگاه اندازهگیری استرس چندسنسوره برای مقطع کارشناسی ارشد شامل 12 اسلاید با سبک مدرن، ساده و مینیمال. مخاطب اساتید و اعضای هیئت علمی هستند. ساختار شامل: عنوان، مقدمه، هدف پروژه، معرفی دستگاه، سنسور ضربان قلب، سنسور حرارتی، سنسور واکنش پوستی، ترکیب دادهها، نرمافزار تحلیل داده، نتایج آزمایشی، مزایا و محدودیتها، نتیجهگیری و پیشنهادها.
This presentation outlines a multi-sensor device for precise stress measurement, targeting academic audiences. It covers introduction, objectives, sensor details (HR, thermal, GSR), data fusion, analy
The slide features the title "Multi-Sensor Stress Measurement Device," highlighting an innovative tool for detecting stress through multiple sensors. It serves as the opening for a Master's thesis presentation on advanced stress detection technology.
Master's Thesis Presentation on Advanced Stress Detection Technology
Stress is a common challenge in work and educational environments, making its accurate measurement essential for enhancing health and performance. Traditional stress measurement methods have limitations, highlighting the need for a multi-sensor approach to achieve greater precision and comprehensiveness.
The project aims to develop a precise device for stress detection using multiple sensors, improving measurement accuracy for research applications. It focuses on enhancing ease of use for researchers and integrating sensor data for comprehensive stress analysis.
This section header slide, titled "Introduction to the Device" and numbered 03, provides an overview of the device. It covers the general explanation of its hardware and software components, along with its portable design and mobile connectivity features.
03
توضیح کلی دستگاه: اجزای سختافزاری و نرمافزاری، طراحی قابل حمل و اتصال به موبایل
The slide titled "Heart Rate Sensor" explains how a PPG sensor works by passing light through the skin to measure light absorption, which correlates with heart rate and blood flow changes. It highlights that during stress, an increased heart rate alters the PPG signal, enabling high-accuracy detection for stress assessment.
Source: Photo by Aniket Narula on Unsplash
The slide introduces a thermal sensor that measures skin temperature variations to detect stress-induced thermal changes, enabling precise identification of stress through skin temperature fluctuations. It highlights key advantages like high accuracy and exceptional sensitivity, along with easy integration into multi-sensor systems for comprehensive analysis.
The slide titled "Skin Response Sensor" (سنسور واکنش پوستی) features an image illustrating a device that measures changes in skin's electrical conductivity. It highlights the sensor's responsiveness to stress and emotional excitement, with applications in stress detection devices.
Source: Photo by rosario janza on Unsplash
The slide discusses data fusion methods from sensors, combining information from heart rate, thermal, and skin response sensors using techniques like Kalman Filter and Bayesian Networks to integrate data, reduce noise, and improve stress level estimation accuracy. It also covers synchronization algorithms such as Cross-Correlation and Dynamic Time Warping, which align sensor signals, compensate for time delays, and enhance overall system precision in dynamic environments.
| روشهای فیوژن داده از سنسورها | الگوریتمهای همگامسازی برای دقت بیشتر |
|---|---|
| روشهای فیوژن داده شامل ترکیب اطلاعات از سنسورهای ضربان قلب، حرارتی و واکنش پوستی است. تکنیکهای رایج مانند Kalman Filter و Bayesian Networks برای ادغام دادهها و کاهش نویز استفاده میشود، که منجر به تخمین دقیقتر سطح استرس میگردد. | الگوریتمهای همگامسازی مانند Cross-Correlation و Dynamic Time Warping برای هماهنگسازی سیگنالهای سنسورها به کار میرود. این روشها تأخیرهای زمانی را جبران کرده و دقت کلی سیستم را افزایش میدهند، به ویژه در محیطهای پویا. |
The software for data analysis processes and filters sensor signals, extracts key features from the data, and applies machine learning algorithms for classification. It enables high-accuracy categorization of stress levels based on these insights.
The slide presents experimental results highlighting a 95% accuracy in stress detection achieved during tests. It also notes that 50 participants were involved in the validation study, with the method showing a 20% improvement over standard approaches.
Achieved in experiments
Validation study group
Comparison with methods
The slide outlines the advantages of a non-invasive stress measurement device that accurately assesses stress without direct contact, using multiple sensors like heart rate, thermal, and skin conductance for comprehensive clinical analysis. It also highlights limitations, including sensitivity to user movement and environmental factors that reduce accuracy, the need for regular calibration, and restricted performance in noisy or electromagnetically interfered settings.
| مزایا | محدودیتها |
|---|---|
| این دستگاه غیرتهاجمی است و بدون نیاز به تماس مستقیم، استرس را با دقت بالا اندازهگیری میکند. ترکیب سنسورهای چندگانه مانند ضربان قلب، حرارتی و واکنش پوستی، تحلیل جامعی ارائه میدهد و برای کاربردهای بالینی مناسب است. | حساس به حرکت کاربر و عوامل محیطی است که میتواند دقت را کاهش دهد. نیاز به کالیبراسیون منظم دارد و در محیطهای پرنویز یا با تداخل الکترومغناطیسی، عملکرد آن محدود میشود. |
The slide summarizes key findings by highlighting the effective detection of stress using multi-sensor technology. It offers recommendations for integrating advanced artificial intelligence and exploring clinical applications, while thanking the audience.
خلاصه یافتهها:
پیشنهادات:
تشکر از مخاطبان
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