The main objective of this project is the early detection of Diabetic Peripheral Neuropathy by a non-invasive method. Diabetic neuropathy is a common and serious complication of diabetes. As Diabetes can harm the nerves, it is called as Diabetic Neuropathy. Early detection and treatment of any disease is an important step towards reducing serious complications. Diabetic Neuropathy is of four types- Peripheral Neuropathy, Autonomic Neuropathy, Proximal Neuropathy and Focal Neuropathy. Diabetic Peripheral Neuropathy is a common problem that causes loss of sensation and uncontrolled nerve and blood vessel damage which is caused by high glucose level. This proposed idea provides a solution to detect Diabetic Peripheral Neuropathy prior to the severe onset of the disease.
CURRENT STATISTICS OF DIABETES IN INDIA:India has one of the highest prevalence of diabetes in the world. It is estimated that by 2030, there will be nearly 80 million Indians with diabetes in the country. Hence this disease has constituted a substantial burden for both the people and health care system prevailing in India. The prevalence of Diabetic Peripheral Neuropathy (DPN) varies greatly ranging from 8% to 59% and is estimated to increase further in the future. Hence screening and early diagnosis has become important to reduce the instance of diabetes to the maximum possible limit.
A simple model that can be used for checking patients for Diabetic Peripheral Neuropathy in legs has been proposed. The symptoms that cause Peripheral Neuropathy are tingling, numbness, burning and pain. Of these, the most common issue is the numbness. Hence, the evaluation of thermal and vibration sensation in patient’s legs are very important. Hence, an external stimulus in the form of temperature and vibration is given to the patients’ foot. Here, two insole pads have been used. The feet are placed on the insole pad to evaluate the thermal and vibration sensation at the six points in the patient’s feet by giving a temperature and vibration stimulus. The temperature stimulus is given in the top panel and the vibration stimulus is given in the second panel below it. After the temperature stimulus is given to the user, the top panel slides sideways automatically for proceeding with vibration stimulation. There are three switches provided at the top of the model through which the patient intimates their responses when the stimulations are given. And also, there is a touch display above the switches in which the response of the patients will be displayed in the tabulated form. Based on this response, Diabetic Peripheral Neuropathy is evaluated.
There will be six regions in each leg. In each region temperature and vibration perception is recorded.
TEMPERATURE MODE:Initially, each region is set with fixed 25°C and then after 2 second the same region is set with 23°C the temperature difference is 2, likewise if it is set with 21°C, 19°C, 17°C, 15°C the temperature difference is 4, 6, 8, 10 respectively. The peripheral neuropathy can be screened and tracked based upon the smallest temperature difference the patient can discern to establish a baseline(25°C). If the temperature difference is 4 or 6 then the patient is likely to have no risks of the disease. If the temperature difference is nearing 10 then the patient has poor sensitivity and needs high medication which states that the patient is prone to the disease.
Vibration perception is screened by 5 amplitudes of vibration at a frequency that emulates a standard tuning fork. If the patient has a loss of sensation to the amplitude level 5 and 4 it indicates nerve damage (i.e.) peripheral neuropathy for diabetic patient. If the patient has a loss of sensation to the amplitude level 3 and 2 it indicates early stage of peripheral neuropathy.
The model that has been designed for evaluating the loss of sensation in the Diabetic patient is shown below. The six pressure points are detected by the color sensor attached to the setup. The color stickers are placed at the pressure points in patient’s feet. The main step involves the calibration of the device which includes the zig-zag movement of the color sensor. Once the color sensor detects the color sticker, it stops and provides the stimuli at that point. The constructed model has a common holder which moves horizontally and vertically across the patient’s feet.
The five probes are of plug-in type which are plugged in to the common holder during the evaluation of the respective parameters.
The touch probe has a key-fob like structure which is used to provide the sensation of touch.The touch probe that is shown in below does not have any electronic components embedded inside it. It has an aluminium structure placed inside the probe in which the tip of the structure goes in contact with the patient’s feet for them to perceive the touch sensation.
The patient experiences a tingling sensation by passing a current in the range of 1-5mA.
The heat probe is shown below. The length and width of this probe are 14.5 cm and 4.5 cm respectively. This probe is a 3D printed probe that is made of a plastic material called PLA (Polylactic acid). In this probe, thermostat module and peltier module have been incorporated which provides the heat stimulus to the patient’s feet. The thermostat module consists of temperature sensor, keys, LED display and a relay. The keys are used to set the temperature which will be displayed in the LED display, relay is used to switch ON/OFF the module. The peltier module is embedded at the end of the probe which is covered with a copper sheet which has good thermal conductivity. When, it comes in contact with the patient’s feet, it provides the stimulation. Different temperatures ranging between 30°C to 50°C are given.
The cold probe is shown below. The length and width of this probe are 14.5 cm and 4.5 cm respectively. This probe is a 3D printed probe made of PLA material same as that of heat probe. In this probe, thermostat module, peltier module, cooler fan and heat sink have been incorporated to give the cold stimulus to the patient’s feet. Similar to the heat probe, the peltier module is embedded at the end of the probe which is covered with a copper sheet which has good thermal conductivity and when, it comes in contact with the patient’s feet, it provides the stimulation. Different temperatures ranging between 0°C to 25°C are given.
The vibration probe is shown below. A structure made of aluminium is incorporated inside the 3D printed plastic probe. A vibration motor is placed at one end of the probe which gives different frequencies of vibration ranging between 4 to 18 Hz. The vibration is transmitted from the vibration motor at one end to the tip of the aluminium structure which goes in contact with the patient’s feet to provide the vibration stimulus. To regulate the appropriate frequency of vibration to be delivered, speed regulator has been used. Aluminium material has been chosen because it is light in weight and also distributes the vibration uniformly to the end of the probe.
Microcontroller reads the date and time from RTC and writes onto the SD card so that the date and time will also be stored in SD card along with the patient's response. The data stored in .txt file format. As delimiter (comma) is specified in between the data, this could also be exported to an Excel sheet and could be used for consultation with the doctors for further treatments.
A webpage created using HTML (Hyper Text Markup Language). The data of touch, hot, cold and vibration responses are accessed from ThingSpeak to the webpage via the tag <iframe> (inline frame). Inline frame has been used to embed ThingSpeak chart within the webpage by the use channel ID that is mentioned in the tag. Once after the patient’s information and data have been updated, the webpage can be downloaded in .pdf file format. This can be used for further references with doctors for treatment.
The icon that has been created for the mobile application is shown in the gif below. The first screen in the app is the “Login” screen in which the user has to enter the User Name and Password. When the button ‘Login’ is pressed, the next screen opens, if the username and password is correct. If not, a pop-up notification showing “The password is incorrect” is displayed on the screen. The second screen is the “patient Info” screen in which the details of the patient such as Name, Gender and Age are given. The patient’s info is displayed in the following screens by the use of TinyDB (Tiny DataBase). It is a non-visible component that is used to store the data so that it can be retrieved and displayed in multiple screens. When the button ‘Next’ is pressed, the next screen opens up. The third screen is the “Test Result-Touch” in which the response of the patient to touch stimulus is displayed in the selected region, say R1. In the region selected, ‘✓’or ‘X’ is displayed indicating whether the touch stimulus is felt or not felt respectively. When the ‘Right Arrow’ button is pressed, the next screen (Screen 4) opens, which is the “Test Result-Hot” screen. In this screen, the temperature value in degree Celsius (30°C-50°C) is displayed in the region selected. Once the ‘Right Arrow’ button is pressed, the next screen (Screen 5) opens which is the “Test Result-Cold” that shows the temperature value in degree Celsius (0°C-25°C) in the region selected. On pressing the ‘Right Arrow’ button, the next screen (Screen 6) opens which is the “Test Result-Vibration” screen. In the selected region, the level of vibration (1V-5V) that the patient could sense is displayed. The data of patient’s response to touch, hot, cold and vibration stimuli are retrieved from ThingSpeak to screens 3, 4, 5 and 6 respectively by the use of Channel ID, Field number and Read API key and are displayed in the corresponding region selected. The last screen is the “Test Report” screen which indicates the stage of severity to each stimulus. When the button ‘result’ is pressed, the stage of severity is indicated with an arrow pointing to the color bars stating “Low Risk” or “Moderate Risk” or “High Risk. A net result is shown as “Low Risk” or “Moderate Risk” or “High Risk” considering the risk stage for all the stimuli.
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