IoT Paralysis Patient Health Care Project

This guide will help you create an IoT-based health care system for paralysis patients. The system will monitor vital signs such as heart rate and body temperature, and provide alerts for timely medical assistance. By integrating various sensors and communication technologies, you can enhance the quality of care for paralysis patients.

Components Required

• Microcontroller (e.g., Arduino or ESP32)
• Heart rate sensor
• Temperature sensor
• Pulse oximeter (optional, for additional health metrics)
• Wi-Fi or GSM module (for communication)
• Power supply (for the microcontroller and sensors)
• Cloud service account (e.g., ThingSpeak, AWS IoT, or Azure IoT)
• Alerting system (e.g., buzzer or notification module)

Setting Up the Hardware

Follow these steps to set up the hardware:

1. Connect the Sensors

   Wire the heart rate sensor and temperature sensor to the microcontroller. If using a pulse oximeter, connect it as well. These sensors will provide vital signs data needed for monitoring the patient's health.

2. Integrate the Communication Module

   Connect the Wi-Fi or GSM module to enable communication between the microcontroller and the cloud service. This will allow you to send data and receive alerts remotely.

3. Set Up the Alerting System

   Connect a buzzer or other alerting system to the microcontroller to notify caregivers or patients of critical health conditions.

4. Power the System

   Ensure all components are properly powered. Use a reliable power supply for the microcontroller and sensors.

Programming the Microcontroller

Write the code to read data from the sensors, process the data, and send it to the cloud. Below is a basic outline of the code using Arduino IDE:

                #include <WiFi.h>  // For ESP32 or ESP8266
                #include <ThingSpeak.h>

                // Configuration
                const char* ssid = "YOUR_SSID";
                const char* password = "YOUR_PASSWORD";
                const char* apiKey = "YOUR_THINGSPEAK_API_KEY";
                const int channelID = YOUR_CHANNEL_ID;

                // Define pins
                const int heartRateSensorPin = A0;
                const int temperatureSensorPin = A1;
                const int alertPin = 5;

                void setup() {
                    Serial.begin(115200);
                    WiFi.begin(ssid, password);
                    while (WiFi.status() != WL_CONNECTED) {
                        delay(1000);
                        Serial.print(".");
                    }
                    Serial.println("Connected to WiFi");
                    ThingSpeak.begin(client);
                    pinMode(alertPin, OUTPUT);
                }

                void loop() {
                    int heartRate = analogRead(heartRateSensorPin);
                    float temperature = analogRead(temperatureSensorPin) * (5.0 / 1023.0) * 100.0;

                    // Example threshold values, adjust as needed
                    if (heartRate < 60 || heartRate > 100 || temperature < 36.0 || temperature > 38.0) {
                        digitalWrite(alertPin, HIGH);  // Activate alert
                    } else {
                        digitalWrite(alertPin, LOW);   // Deactivate alert
                    }

                    // Send data to ThingSpeak
                    ThingSpeak.setField(1, heartRate);
                    ThingSpeak.setField(2, temperature);
                    ThingSpeak.updateChannel(channelID, apiKey);

                    delay(30000);  // Update every 30 seconds
                }
            

This code reads data from the heart rate and temperature sensors, processes it, and sends it to ThingSpeak. The alerting system is activated based on predefined thresholds.

Setting Up Cloud Integration

To visualize and analyze the data, integrate the system with a cloud service. Configure your cloud service to display health metrics and set up notifications or alerts based on the received data.

Testing and Calibration

Test the system by monitoring the health metrics and verifying that the alerting system works as expected. Adjust the sensor thresholds and calibration settings as needed for accurate health monitoring.