A portable device for Nipah virus detection using odor analysis

Abstract

A portable AI-based VOC detection device, consisting of: a portable housing with a micro air intake pump for contactless air sampling, ensuring hygienic sampling; an ionization module that uses UV light to break down VOCs, and a miniature mass spectrometer for the analysis of molecular fragments; a machine learning model trained to detect Nipah virus-specific VOC signatures and to identify unknown or emerging disease patterns in order to warn users of potential health risks; a detection indicator system with LED display and acoustic alarm system for real-time notifications of detection results; and a wireless communication and power supply system with WLAN connectivity for AI model updates, as well as a rechargeable lithium-ion battery for low power consumption and high efficiency.

Description

TECHNICAL FIELD

[0001] The present invention combines machine learning and diagnostic technology to develop a wearable device capable of detecting viruses such as Nipah through odor analysis. The device analyzes the volatile organic compounds (VOCs) in a person's breath. If it detects specific biomarkers associated with a virus, it can confirm its presence. Even if these biomarkers are absent, the AI ​​examines the overall pattern and percentage of VOCs to diagnose the disease. This makes the device useful not only for detecting Nipah but also for identifying other diseases. BACKGROUND

[0002] According to health records, several outbreaks of the Nipah virus have occurred in Malappuram, Kerala. Significant cases were reported in 2018, 2019, and 2023. The virus, which is primarily transmitted from fruit bats to humans, has a high mortality rate and spreads through direct contact.

[0003] The first major outbreak occurred in 2018 in the districts of Kozhikode and Malappuram, resulting in 17 deaths out of 18 confirmed cases, representing a mortality rate of approximately 95%. However, subsequent outbreaks saw significant decreases in both case numbers and mortality rates due to improved medical care and containment measures such as contact tracing and quarantine protocols.

[0004] Infectious diseases such as Nipah pose a serious risk to public health due to their high mortality rates and potential for rapid spread.

[0005] Currently, diagnostic procedures such as PCR (polymerase chain reaction) and ELISA (enzyme-linked immunosorbent assay) are still considered the gold standard for the detection of pathogens.

[0006] However, these methods require laboratory infrastructure, trained personnel and significant processing times, which delays early diagnosis that is crucial for containing outbreaks.

[0007] Recent research highlights the potential of volatile organic compounds (VOCs) as biomarkers for disease detection. Viral infections alter the host's metabolic pathways and lead to the release of specific VOCs in breath, sweat, and other bodily excretions. Respiratory infections, for example, can cause detectable changes in exhaled VOC profiles.

[0008] Conventional electronic noses (e-noses) were developed to analyze such VOCs, but their application was limited due to their inability to detect unknown pathogens and their reliance on predefined VOC libraries.

[0009] Given these limitations, there is a great need for an advanced, portable and intelligent diagnostic device that can detect both known and emerging pathogens by learning and adapting to new VOC patterns in real time.

[0010] Such a system would enable non-invasive, rapid and accurate detection of pathogens and would therefore be particularly useful in remote and resource-poor environments.

[0011] By facilitating early detection, this invention could make a crucial contribution to containing future disease outbreaks and improving public health measures. GOAL OF THE INVENTION

[0012] The main objective of the present invention is to provide a portable, AI-controlled diagnostic device that can detect viral pathogens, including the Nipah virus, by odor analysis of volatile organic compounds (VOCs).

[0013] A further objective of the present invention is to provide a non-invasive diagnostic method that detects pathogens in exhaled or ambient air, thus eliminating the need for blood tests or swabs. A further objective of the present invention is to provide a system and method for real-time detection that enables rapid medical intervention for infection control and the prevention of disease outbreaks.

[0014] Another objective of the present invention is to provide a system and method that integrates AI adaptability and uses machine learning algorithms to detect unknown VOC patterns and identify new pathogens.

[0015] Another objective of the present invention is to provide a system and method that is portable, lightweight and user-friendly, and suitable for field use and remote diagnostics.

[0016] Another objective of the present invention is to provide a system and method that supports the detection of multiple pathogens and enables the updating of AI models with new VOC profiles for enhanced functionality.

[0017] Another objective of the present invention is to provide a cost-effective system and method that reduces dependence on expensive laboratory infrastructure and makes it accessible even in resource-poor environments.

[0018] Further objectives, advantages and features of the present invention will become apparent from the detailed description below, in which various aspects of the invention are illustrated by example. SUMMARY

[0019] The present invention serves for the early detection of viral infections such as Nipah. It identifies diseases by analyzing unique odor patterns (VOCs) emitted by infected individuals. This makes the process fast, non-invasive, and efficient. A key feature is its ability to learn and adapt. If the device detects an unknown pattern, the AI ​​model updates itself, thereby improving accuracy over time. The device delivers real-time results on a user-friendly interface, thus supporting medical professionals in making faster decisions. Thanks to its lightweight and portable design, the device can also be used in hospitals and remote locations without laboratory facilities. Through its fast, precise, and easily accessible method of disease detection, it makes a significant contribution to the prevention of disease outbreaks and the improvement of medical diagnostics. BRIEF DESCRIPTION OF THE DRAWING

[0020] The further objectives, features and advantages will become apparent to the person skilled in the art from the following description of the preferred embodiment and the accompanying drawing. Fig. The portable device for Nipah virus detection by means of odor analysis according to an embodiment of the present invention is shown schematically.

[0021] The specific features of the present invention are illustrated in some drawings, but not in others. This is solely for the sake of clarity, since each feature can be combined with all or some of the other features of the present invention. DETAILED DESCRIPTION

[0022] The various components, as well as the other innovations and functions, are explained in detail below: The breath analysis system gently extracts air samples from patients, ensuring a comfortable testing procedure. The device's air intake module takes air samples from the exhaled breath of potentially at-risk patients. It is equipped with pre-filters that remove dust and irrelevant particles, so that only VOC-rich air samples reach the odor molecule detection unit. This ensures that external environmental factors do not interfere with the device's analysis. The odor molecule detector then processes the extracted air using miniaturized mass spectrometry, which can convert VOCs into unique molecular signatures.These molecular profiles are then transmitted via a microcontroller to the AI-driven analysis module, which compares the detected VOC patterns with pre-trained datasets of known pathogens such as Nipah. If there is a match, the device outputs a positive result. This is what makes the device so unique: its adaptability. If the VOC patterns do not match any of the existing profiles, an AI algorithm takes over the assignment of the unknown patterns using unsupervised learning. In turn, the device learns to update its database independently.

[0023] The present invention describes a portable device for detecting the Nipah virus. The device consists of a handheld housing with a micro air intake pump for contactless air sampling, ensuring hygienic sample collection. The ionization module uses UV light to degrade volatile organic compounds (VOCs), and a miniature mass spectrometer analyzes molecular fragments. The machine learning model is trained to recognize Nipah virus-specific VOC signatures and identify unknown or emerging disease patterns to warn users of potential health risks. The detection display system features an LED indicator and an audible alert system for real-time notification of results. The wireless communication and power supply system provides Wi-Fi connectivity for AI model updates and a rechargeable lithium-ion battery for low power consumption and thus high efficiency.The present invention will contain the spread of disease and improve public safety. This feature makes the device essentially relevant and effective against emerging pathogens—a highly powerful tool for dynamic health crises. Results are displayed on a user interface that presents the findings in real time. It can show detection results, alerts for unknown VOC patterns, battery level, and error messages. The device is powered by a lightweight, rechargeable battery, making it highly portable and suitable for use in hospitals and remote areas. Its compact size and light weight allow for easy transport and convenient use in clinics and hospitals. The rechargeable battery ensures uninterrupted operation, making it a reliable tool for field staff and for field testing.Its compact design ensures easy handling by medical professionals. In summary, PathoSniff offers a fast and painless method for diagnosing the Nipah virus and is a practical and useful screening device for both doctors and patients. Since no blood draws or laboratory tests are required, it reduces waiting times, discomfort, and testing costs, making early diagnosis more convenient and accessible. Reference symbol list: 1. Micro air intake pump 2. Pre-filter (removes dust) 3. Ionization module 4. Mini mass spectrometer 5. Microcontroller 6. AI-based pattern recognition module 7. Digital display 8. Power supply 9. Housing 10. Air outlet 11. Handle

Claims

[1] A portable AI-based VOC detection device consisting of: a portable housing with a micro air intake pump for contactless air sampling, ensuring hygienic sampling; an ionization module that uses UV light to break down VOCs, and a miniature mass spectrometer for the analysis of molecular fragments; a machine learning model trained to detect Nipah virus-specific VOC signatures and to identify unknown or emerging disease patterns in order to warn users of potential health risks; a detection indicator system with LED display and acoustic alarm system for real-time notifications of detection results; and a wireless communication and power supply system with WLAN connectivity for AI model updates, as well as a rechargeable lithium-ion battery for low power consumption and high efficiency. [2] Device according to claim 1, wherein the air intake module is equipped with pre-filters to remove dust and irrelevant particles so that only VOC-rich air samples enter the odor molecule detection unit.

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