NBME

Hardware Research

 Early detection and rapid diagnosis of diseases have drawn much attention in today’s medical practice. Many diseases such as cancer may have a high chance of full recovery if detected at early stages. This paper proposes a miniature electronic nose (e-nose) for breath analysis. The proposed e-nose is composed of a sensor array, signal processing, and artificial intelligence. The conductive gas sensor is a microheating sensing device deposited by nanomaterials. The sensor signal is processed by an AI edge accelerator based on computing-in-memory (CIM) architecture......

Algorithm Research

 Early detection and rapid diagnosis of diseases have drawn much attention in today’s medical practice. Many diseases such as cancer may have a high chance of full recovery if detected at early stages. This paper proposes a miniature electronic nose (e-nose) for breath analysis. The proposed e-nose is composed of a sensor array, signal processing, and artificial intelligence. The conductive gas sensor is a microheating sensing device deposited by nanomaterials. The sensor signal is processed by an AI edge accelerator based on computing-in-memory (CIM) architecture......

Application

 This study developed an electronic nose (E-nose) system to detect the smell of coffee beans, aiming to address the lack of a convenient screening method for identifying stale beans. The system consists of an environmental control system, a sensor array, and a data signal readout system. By recognizing the smell of coffee beans, it can distinguish various degrees of mold contamination. Gas samples were collected from coffee beans in a controlled environment, and changes in signals from the sensor array were recorded after introducing the target gas. Features were extracted from the data, followed by dimensionality reduction using techniques like principal component analysis and linear discriminant analysis to reduce complexity and eliminate noise......

Application

 Lung cancer is one of the leading fatal diseases that causes millions of deaths each year, but early detection and treatment can improve survival. Electronic nose (e-nose) is a recently developed gas sensor that can help us obtain information from the exhaled breath of patients. Its advantages include low cost and no residual radiation risk. Our classifier uses Convolutional Neural Network(CNN) architecture for diagnosing lung cancer based on analyzing e-nose sensory signals.......

Application

Spoilage Degree Detection

Trimethylamine

Hydrogen Sulfide

Histamine

Application

Wheeled Mobile Robot

Concentration, Wind Direction, Wind Speed

Enhance Efficiency & Success Rate

Explosive, Toxic Gas, Fire Exploration

Application

 Electronic nose (E-nose) systems have become popular in food and fruit quality evaluation because of their rapid and repeatable availability and robustness. In this paper, we propose an E-nose system that has potential as a non-destructive system for monitoring variation in the volatile organic compounds produced by fruit during the maturing process. In addition to the E-nose system, we also propose a camera system to monitor the peel color of fruit as another feature for identification. By incorporating E-nose and camera systems together, we propose a non-destructive solution for fruit maturity monitoring. The dual E-nose/camera system presents the best Fisher class separability measure and shows a perfect classification of the four maturity stages of a banana: Unripe, half-ripe, fully ripe, and overripe.......

Application

 Ventilator-associated pneumonia (VAP) is the most frequently acquired infection among patients that receive mechanical ventilation in the intensive-care unit (ICU). The mortality rate for VAP lies in the 20-to-50% range and could be even higher in some ICUs. A standard operation procedure to VAP treatment includes a sequence of chest radiography, sputum gram stain, sputum culture, and empiric therapy, initially with antibiotics covering broad pathogens. However, collection of the gram stain and culture of lower respiratory tract specimen is usually not time-efficient (up to 5 days), delaying the initiation of therapy and unacceptable for critically ill patients. A rapid and accurate diagnosis for VAP is therefore crucial, but still unavailable........

Application

 Chronic obstructive pulmonary disease (COPD) still lacks a rapid diagnosis strategy. In this paper, we propose a low-power nose-on-a-chip for rapid COPD screening. This chip is designed for implementation in a personal handheld device that detects patient breath for COPD diagnosis. The chip has 36 on-chip sensors, a 36-channel adaptive interface with an integrated programmable amplifier, a four-channel frequency readout interface, one on-chip temperature sensor, a two-channel successive approximation analog-to-digital converter, a scalable learning kernel cluster, and a reduced instruction set computing core with low-voltage static random-access memory. This chip is fabricated in 90 nm CMOS and consumes 1.68 mW at 0.5 V. In simulation, the system distinguished between undiseased and diseased patients with 90.82% accuracy for a set of diseases including COPD and asthma and exhibited 92.31% accuracy for identifying patients with COPD or asthma........

Application

 In this paper, we focused on the method of lung cancer identification by breath. Lung cancer had occupied the first place in the top ten leading causes of death. When lung cancer patients were diagnosed, most of the patients had lost the opportunity of cure. However, physicians determined the lung cancer cases in complicated steps. Therefore, the purpose of this breath detection system was to help physicians to quickly screen for rapid screening lung cancer. We used KNN and SVM with leave-one-out cross validation to analyze. Finally, we got good accuracy that was 84.4%.......

Application

 Ketamine severely endangers health and dwelling quality. In Taiwan, one of the common methods of taking ketamine is by smoking ketamine cigarettes. By heating up ketamine cigarettes, it produces an odor that smells similar to burning plastic. There are no effective and convenient methods for immediately detecting and identifying the smell of ketamine cigarettes. Therefore, this research proposed to develop an electronic nose system to identify the gas of ketamine cigarettes. In this study, standard operating procedures were established for collecting ketamine gas and ketamine cigarette gas at constant flow to quantitatively collect those gas samples least affected by environmental factors. After injecting the gas samples, the variation signal of sensor array was noted. By feature extraction and dimensionality reduction algorithms, the complexity of data decreased. The classification results were also analyzed through linear regression and classification algorithms, and the classification accuracy was up to 95.92%........

Application

Tea Leaves Stages Monitoring

Process Time Determination

Application

Air Quality Monitoring Module

Detection Limitation (Ammonia: 0.25ppm)

Recording Distribution in NTHU