NON-INVASIVE WEARABLE GADGET FOR EARLY DETECTION OF ELEPHANTIASIS

Abstract

ABSTRACT OF THE INVENTION This invention is a non-invasive, portable diagnostic device for early detection of elephantiasis, or lymphatic filariasis. Unlike traditional invasive methods that identify the disease only at advanced stages, this device integrates sensors, including a temperature sensor {l 05), pressure sensor (I 06), electrical impedance sensor (I 08), infrared sensor (I 07), humidity sensor (I 02), pulse oximeter (103), electromyography sensor (101), and accelerometer (104), into _a wearable Velcro strap. These sensors monitor physiological parameters associated with early lymphatic obstruction. An Arduino microcontroller (109) processes real-time sensor data, while a GSM module (113) transmits it remotely to healthcare providers, enabling continuous monitoring and early intervention in underserved areas. Machine learning algorithms analyze this data to identify biomarkers linked to· elephantiasis, enhancing diagnostic accuracy. Affordable, portable, and easy to use, this device is ideal for low-resource settings, providing an accessible, timely diagnostic tool for combating neglected tropical diseases.

Specification

DESCRIPTION:
[000 I) This finding introduces a portable, non-invasive diagnostic tool for the early identification
of lymphatic filariasis, commonly referred to as elephantiasis. Conventional methods of
diagnosing this illness, like tissue biopsies and antigen detection assays, are intmsive and
typically identify the illness only when it is advanced and irreparable damage has already been
caused. The suggested gadget incorporates a Velcro strap with built-in sensors to track vital
physiological indicator$ linked to early-stage elephantiasis. These sensors include temperature,
pressure, electrical impedance, infrared, humidity, pulse oximeter, electromyography (EMG), and
accelerometer. It records minute variations that indicate the onset of the illness before outward.
signs indicate. Continuous remote monitoring by healthcare providers is made possible by the
gadget's use of an Arduino microcontroller to process real-time data from these sensors and send
it via a GSM module. Its uniqne combination of early detedion capability, non-invasiveness,- and
real-time remote monitoring makes it a transforrnative tool for managing elephantiasis. The gadget
is designed for portability, affordability, and ease of use, making it particularly suitable for lowresource
settings and offering an accessible solution in line with global health efforts to combat
neglected tropical diseases. Utilizing diagnostic algorithms enhanced with machine learning, the
system can identify specific biomarkers indicative of early elephantiasis, enabling timely
therapeutic intervention and potentially reducing the disease's severity and socio-economic
burden.
PRIOR ART AND BACKGROUND:
[0002) Several patents exist in the field of wearable devices for non-invasive health monitoring.
This section compares our invention to eight related patents, focusing on innovations in early
detection of elephantiasis through wearable sensor technology. This revision aligns the comparison
with the specific focus on elephantiasis detection using non-invasive methods, such as wearable
gadgets.
[0003) Several patents exist in the realm of wearable health monitoring, posture correction,
wearable sensors and a$sistance to disabled people. This section compares our invention to related
patents:
US9357921B2: Wearable Health Monitoring Systems, describes a wearable device designed to
monitor various physiological parameters continuously. The system includes sensors for tracking
metrics like heart rate, temperature, movement, and other health-related data. The collected data
can be processed in real time, providing insights into a user's health status and potentially alerting
them or healthcare providers to abnormalities. This patent emphasizes the device's applications in
health monitoring, fitness, and early detection of medical conditions, offering a convenient, non
invasive way for users to stay informed about their health. This wearable system can be used in
various environments, including personal, clinical, and sports settings, supporting proactive health
management.
US20100106016Al: Non-Invasive Blood Flow and Pressure Monitors, describes a non-invasive
system for monitoring blood flow and pressure. This invention uses sensors to measure parameters
like blood velocity and pressure in blood vessels, providing continuous and real-time data. By
employing optical or acoustic sensors, the device can monitor these metrics through the skin,
avoiding the need for invasive techniques. This system is intended to help patients with .
cardiovascular conditions by enabling consistent, at-home monitoring, which can lead to earlier
detection of issues and better overall health management. The technology is particularly beneficial
in settings where regular clinical measurements of blood flow and pressure might be impractical.
US20210403986Al: Detection and prediction of infectious disease, focuses on a method for noninvasive
detection and prediction of infectious diseases by ~nalyzing biomarkers found in
accessible body fluids like blood. This technology utilizes molecular diagnostics and
bioinformatics to identify infection-specific markers, providing a rapid and accurate alternative to
traditional, more invasive diagnostic techniques. The approach enables earlier and easier diagnosis
of bacterial, viral, and fungal infections, which can be critical for prompt treatment and better
patient outcomes, especially in resource-limited or remote settings.
US20160235354Al: Methods for detecting, monitoring and treating lymphedema, outlines
methods for detecting, monitoring, and treating lymphedema, a condition caused by lymphatic
fluid buildup resulting in tissue swelling. The invention includes a non-invasive diagnostic system
that uses various sensors to measure parameters like limb volume, fluid retention, and skin
elasticity. These measurements help in early detection and continuous monitoring of lymphedema
progression. Additionally, the patent describes therapeutic interventions, such as compression
garments or devices, which can adjust based on real-time sensor data to manage and alleviate
swelling. This approach aims to improve patient outcomes through proactive monitoring and
personalized treatment strategies.
US6757719Bt: Method and system for data transmission between wearable devices or from
wearable devices to portal, describes a method and system for data transmission between wearable
devices or from wearable devices to a central portal. This invention allows wearable devices to
communicate health and activity data, facilitating real-time monitoring and data exchange. The
system can transmit data over various communication networks, such as Bluetooth, Wi-Fi, or
cellular, enabling wearable devices to share metrics like heart rate, movement, or location with a
central hub for analysis or storage. This system is valuable for applications in health monitoring,
fitness, and emergency response, allowing data to be remotely monitored by healthcare providers
or securely stored in a portal for later access.
US20210398655Al: Machine learning algorithms for detecting medical conditions, related
systems, and related methods, outlines systems and methods for deploying machine learning
algorithms to detect medical conditions. The system uses data from various imaging devices (e.g.,
CT scans, MRis, X-rays) alongside patient health data, including medical history and real-time
clinical information. This integration of diverse data allows the algorithm to make more accurate,
objective medical diagnoses by combining images with patient-specific information like heart rate,
medications, and previous test results. This approach aims to improve diagnostic accuracy and
efficiency by leveraging machine learning to process compl~x. multi-source data set.
US9357958B2: Application of electrochemical impedance spectroscopy in sensor systems,
devices, and related methods, focuses on the use of Electrochemical Impedance Spectroscopy
(E!S) in sensor systems, particularly for continuous glucose monitoring. The patent describes
methods to assess the health of sensor electrodes, detect failure modes, and manage calibration
without frequent invasive tests. It leverages impedance data from r~dunn~n\ P.!P.ctrodeG to improve
diagnostic accuracy, detect contaminants, and monitor electrode conditions. This approach
minimizes the need for fingerstick calibrations and enhances sensor reliability.
OBJECTIVE:
(0004) Objective I: Design and implement suitable sensors integrated with Arduino technology
for the early detection of elephantiasis, eliminating the need for invasive blood tests.
Objective 2: Incorporate a GSM module for real-time transmission of diagnostic data to
healthcare providers, ensuring continuous patient monitoring and prompt medical response.
Objective 3: Develop a portable, user-friendly diagnostic Velcro system that is easy to maintain
and tailored for use in low-resource settings, ensuring broader accessibility and application.
SUMMARY:
(0005) The proposed initiative presents a novel, non-invasive diagnostic tool for the early
identification of elephantiasis, a chronic parasitic disease that is mostly caused on by Wuchereria
bancrofti and causes disfiguring swelling and severe lymphatic blockage. The invasive methods
used in traditional elephantiasis diagnostics, including •s tissue biopsies and blood antigen
detection, usually discover the disease only after considerable physiological damage has been
caused. The goal of this project is to overcome these constraints by creating a wearable, Arduinobased
gadget that can detect minute physiological changes that point to elephantiasis in its
subclinical phases and allow [for prompt treatment. The gadget measures electrical impedance,
temperature, pressure, and other physiological indicators using a mix of specifically selected
sensors that are attached to a Velcro strap. As early markers of lymphatic dysfunction, which
precedes outward swelling and other elephantiasis signs, these metrics are crucial. An Arduino
microcontroller, which powers the sensors and enables real-time physiological data analysis,
processes the data collected by the sensors. The technology can identify subclinical illness stages
before permanent harm arises by detecting early variations from baseline values. The
incorporation of a GSM module, which permits real-time data transfer to healthcare practitioners,
is a distinctive aspect of this project. Even in environments with limited resources and internet
connectivity, GSM technology enables continuous monitoring, guaranteeing that medical
professionals can get real-time updates on the patient's condition. In underserved or remote
locations where access to healthcare is frequently restricted, this capability facilitates timely
medical responses and improves illness management. A major improvement over standard
diagnostics, which typically call for recurring clinic visits, is the gadget's remote monitoring
capability. The gadget is intended for usage in low-resource areas and is made to be portable,
reasonably priced, and simple to use. Patients can wear the gadget with case and little supervision
owing to the comfort and flexibility offered by the Velcro strap. The design's ease of use and
accessibility guarantee wider adoption and aid international health initiatives, especially in
tropical areas where elephantiasis is most common.
[0006] This project is innovative because it combines disease-specific, non-invasive sensors with
real-time monitoring and data transmission capahilit.i~.• 10 provide a gamc-chn11ging sululiun rhat
tackles t.he logistical and diagnostic difficulties associated with elephantiasis detection and
management. By facilitating early detection, slowing the progression of the disease, and
eventually enhancing patient outcomes and quality of life, this gadget has the potential to greatly
Jessen the effect of the illness.
DETAILED TECHNICAL DESCRIPTION:
[0007] The main goal of the proposed research is to create a wearable, non-invasive diagnostic
tool for the early identification of lymphatic filariasis, often known as elephantiasis. The disease
elephantiasis, which is brought on by parasitic worms like Wuchereria bancrofti, causes extreme
swelling, irreparable physical abnormalities, and gradual lymphatic blockage. Conventional
diagnostic methods, such as tissue biopsies and blood antigen testing, are intrusive, uncomfortable
for patients, and typically identify the disease later on. By combining cutting-edge sensor
technology with an Arduino microcontroller, this project presents a practical, affordable, and easyto-
use tool for the early, non-invasive identification of this crippling illness.
[0008] Gadget Design and Sensor Array Integration
A Velcro-based wearable strap with a variety of carefully selected sensors integrated to record
physiological data linked to early-stage lymphatic blockage is used in the diagnostic tool.
The primary sensors include:
I. Temperature Sensor: Elevated body temperature is a common early sign of
inflammation and lymphatic response in affected tissues. The gadget uses a temperature
sensor (such as the LM35 or DHT22) to measure any localized temperature rise,
indicating possible subclinical immune activity. The temperature data, processed
continuously, enables early detection of abnormal thermal patterns linked to elephantiasis
progression.
2. Pressure Sensor: This sensor (such as BMP280) records subclinical increases in tissue
fluid pressure by detecting pressure changes brought on by early swelling brought on by
lymphatic obstruction. The real-time monitoring of these pressure variations is critical in
detecting disease at stages before visible swelling occurs, offering a preventive approach
to diagnosis.
3. Electrical Impedance Sensor: Tissue impedance measurements are used to ass~ss
electrical conductivity, which varies with fluid retention and tissue composition. By
capturing subtle changes in impedance, the gadget can identify abnormal fluid
accumulation linkerl to early lymphatic dy5fuucliun. This sensor thus provides· an
essential physiological marker for elephantiasis, complementing the data from
temperature and pressure sensors.
4. Additional Sensors: Optional sensors, such as a pulse oximeter (MAX30100) or
accelerometer (MPU6050), can be added to monitor additional health parameters,
providing a comprehensive health profile that can be useful for differential diagnosis or
detecting comorbidities that affect the lymphatic system.
These sensors are connected to an Arduino microcontroller (such as the Arduino Nano ),
which acts as the central data-processing unit. The Arduino is programmed to receive data from
each sensor, perform initial signal conditioning, and store the data for analysis. By combining
data from multiple sensors, the system can detect early, subtle physiological changes associated
with elephantiasis. The use of Arduino technology makes the gadget both affordable and
adaptable, essential qualities for implementation in low-resource settings.
[0009] Real-Time Data Transmission with GSM Module
A GSM module (e.g. the SIMSOOL) is incorporated into the gadget to facilitate continuous and
remote monitoring, allowing real-time data transmission to healthcare providers a feature that is
especially useful in remote and low-resource regions where access to routine healthcare checkups
may be limited. The GSM module transmits the physiological data collected from the sensors
to a secure cloud server or directly to the gadgets of healthcare professionals, allowing them to
monitor the patient's status and react quickly to any abnormal readings. The proactive,
telemedicine-based approach to disease management made possible by the real-time data transfer
helps close the gap between patients in underprivileged areas and medical professionals. The
GSM module operates over mobile networks, making it accessible even in areas with poor
internet connectivity, in contrast to Bluetooth or Wi-Fi modules which require to be close to a
router. This technology's early intervention helps in lowering the probability of severe disease
developments and improves patient outcomes.
[00 I 0] Data Processing and Machine Learning Integration
The integration of machine learning algorithms is the key innovation of this system for predictive
analytics. Data collected from both healthy and infected people are used for training the machine
learning models for detecting patterns indicating early-stage infection. By applying supervised
learning techniques, the system can differentiate between normal physiological variations and
early pathological changes, improving diagnostic specificity and sensitivity. The Arduino
processes raw sensor data and transmits it to a cloud-based server for machine learning analysis,
where algorithms identify early biomarkers of elephantiasis, such as deviations in temperature,
pressure, impedance, infrared, humidity, pulse oximetry, electromyography (EMG), and
accclerometry. This allows the system to r.nntinuously "loam" from ilcw palienr data, retmmg its
diagnostic accuracy over time. The machine learning model provides a diagnostic score that
healthcare providers can use to determine the likelihood of elephantiasis, enabling data-driven
decision-making in a clinical setting.
[0011] Portable, User-Friendly, and Accessible Design
The gadget is designed to be compact, lightweight, and eAsy to wear, using a Velcro strap to secure
the sensor array to the body. This design choice not only ensures comfort and ease of use for the
patient but also facilitates quick setup and adjustment by healthcare workers with minimal training.
The Velcro strap and modular sensor setup make it easy to maintain and replace components,
extending the gadget's longevity and suitability for harsh environments often encountered in
tropical regions where elephantiasis is prevalent. A rechargeable .battery pack powers the gadget,
ensuring prolonged use without frequent recharging. This feature is crucial for applications in
remote areas, where electricity may be unreliable. All components are selected with cost and
durability in mind, making the gadget affordable for mass production and accessible to healthcare
providers in resource-limited settings.
[00 12] Novelty and Technical Innovation
The novelty of this system relies on its non-invasive, multi-sensor approach for detecting the
early stages of elephantiasis infection. The conventional methods are mostly invasive such as
detection of antigen from blood samples, where the infection can be identified only after the
occurrence of the symptoms.
Whereas, this system helps in detecting the lymphatic changes in the early stages of infection even
before the visible symptoms occurs. Thus, it enable us to provide preventive treatment options
which aids in reducing the infection's severity and adverse effects. In addition, the system becomes
unique by integrating them with GSM-based real-time data transmission especially build for using
in regions having poor internet connection.
Moreover, the integration of GSM-based real-time data transmission makes this gadget unique,
particularly for regions lacking internet connectivity. This feature provides a continuous
monitoring solution that is otherwise absent in traditional diagnostics, ensuring timely healthcare
intervention. The use of machine learning to analyse multi-sensor data for disease-specific patterns
further distinguishes this project by providing personalized, data-driven insights for elephantiasis
diagnosis.
ORA WING NUMERALS
(I 0 I) - Electromyography sensor
(I 02)- Humidity sensor
(103)- Pulse oximeter
(I 04) - Accelerometer
(I 05)- Temperature sensor
(I 06) - Pressure sensor
(I 07) - Infrared sensor
(I 08)- Electrical impedance sensor
(I 09)- Arduino Uno
(II 0)- Power supply
(111)-MemoryUnit
( 112)- Display
(113)- GSM Module
(114)- Cloud Server
(115)- Phone
BRIEF DESCRIPTION OF THE ORA WING:
(0013] The block diagram denotes the system architecture for non-invasive diagnostic system
integrated with Arduino Uno microcontroller along with multiple sensors to monitors various
physiological parameters, providing collective data. for early detection of elephantiasis. The
following are the description of each component and its function:
I. Sensors:
(101) Electromyography Sensor: The abnormalities or changes in the functioning of muscles can
be detected by measuring the electrical activity in muscles.
(102) Humidity Sensor: The level of moisture content in the surrounding environment can be
measured using this, for assessing the skin conditions.
(1 03) Pulse Oximeter: The circulatory health can be indicated by tracking the blood oxygen levels
and heart rate.
(104) Accelerometer: It helps m evaluating the mobility or swelling by measuring the body
movement or its position.
(105) Temperature Sensor: The local temperature changes due to inflammation can be detected for
identifying the early signs of inflammation due to infection.
(1 06) Pressure Sensor: The fluid pressure can be measured for detecting the changes linked with
lymphatic blockages.
(107) Infrared Sensor: The skin temperature or blood flow in the body can be assessed directly
without contact measurements.
(108) Electrical Impedance Sensor: The fluid retention and lymphatic dysfunction can be identified
by measuring tissue impedance.
2. (109) Arduino Uno:
- Acts as the central control unit, collecting data from each sensor and processing it for analysis
by empowering each sensor as well as maintains the rl~t~ flow within the ny3tcm.
3. (110) Power Supply:
- Provides the required energy for operating the Arduino Uno (I 09) and its connected sensors.
4. (112) Data Storage and Display:
- (111) Memory Unit: Stores collected sensor data for analysis and review, allowing for tracking
changes over time.
- (112) Display: Provides real-time feedback or status updates to the user, allowing for immediate
monitoring.
5. (113) GSM Module:
- Enables remote data transmission by sending processed data to a Cloud Server (114). This
module supports real-time remote monitoring, especially useful in telemedicine or for patients in
remote locations.
6. (114) Cloud Server and Mobile Access:
- The Cloud Server (I 14) receives data from the GSM module (113), storing it securely and
making it accessible to healthcare providers.
-Data on the cloud can be accessed through a Phone ( 115) or other devices, allowing healthcare
providers to monitor patient data remotely.
This setup provides a comprehensive, remote diagnostic solution that collects, processes, and
transmits physiological data, enabling early detection and continuous monitoring of conditions like
elephantiasis.

CLAIM:
1/WE Claim,
I. A non-invasive diagnostic gadget for detecting early-stage elephantiasis, comprising:
o A Velcro strap embedded with temperature sensor (I 05), pressure sensor (I 06),
electromyography sensor ( 10 I), humidity sensor (I 02), accelerometer ( 104),
infrared sensor (107), pulse oximeter (103) and electrical impedance sensor (108)
configured to monitor physiological parameters indicative of elephantiasis;
o An Arduino microcontroller (I 09) connected to the sensors for real-time data
processing;
o A GSM module (113) for remote data transmission to healthcare providers.
2. The system of claim 1, wherein the temperature sensor (I 05) is .configured to detect
localized temperature increases associated with inflammation or lymphatic response in
early elephantiasis stages.
3. The system of claim 1, wherein the pressure sensor (106) is adapted to measure fluid
pressure changes due to lymphatic blockage, enabling detection before visible swelling
occurs.
4. The system of claim 1, wherein the electrical impedance sensor (I 08) is configured to
detect tissue impedance variations associated with fluid retention and lymphatic
dysfunction, providing an early marker for elephantiasis.
5. A method for monitoring elephantiasis progression using the system of claim 1,
comprising:
o Attaching the Velcro strap to the patient; Collecting and analysing sensor data to
detect deviations from baseline physiological values;
o Transmitting analysed data through the GSM module ( 113) to healthcare providers
for continuous monitoring.
6. The system of claim 5, wherein machine learning algorithms are applied to identify
patterns in sensor data that correlate with early elephantiasis markers.
7. A system for remote monitoring of elephantiasis using the system of claim I, wherein
the GSM module (I 13) transmits data to a cloud server (114) accessible by healthcare
professionals, enabling real-time patient monitoring regardless of geographic location.
8. The system of claim 1, further comprising a portable battery pack designed to support prolonges, continous use in law source settings.

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