When you think about healthcare, the first thing that comes to mind is a doctor with a stethoscope hanging around his or her neck. The first advice you get from your friends whenever you mention your health is, ‘go to hospital’ or ‘go see a doctor’. This is good advice. However, wouldn’t it be great if you didn’t have to go to the hospital every time you needed to check your heart rate, body temperature or blood pressure? Well, the good news is that this is already a reality, thanks to open-source healthcare platforms and sensors.
A lot can be said about a person’s health by looking at his or her biometrics. In fact, ancient and modern medical prognosis techniques have one thing in common. They both rely on the analysis of body characteristics. So, how are these characteristics detected?
There are many kinds of measurements that can be retrieved from the body. One needs to use specialized equipment to do that. For a long time such equipment was expensive and not in the public domain. To access it, one had to go to a medical facility. However, this has changed. The introduction of open source healthcare platforms and sensors has led to the development of simple, cheap and easy to use biometric equipment. Here are some examples of such platforms and sensors.
Bitalino is a popular open-source biomedical development platform that has a variety of biometric sensors. Some of those sensors include Electromyography (EMG) sensor, Electrocardiography (ECG) sensor, LUX sensor, Accelerometer and Electro Dermal Activity (EDA) sensor. In addition to the sensors, the platform offers an Atmega328 microcontroller for processing the sensor readings and a Bluetooth module for wireless communication.
To make the kit more versatile, each module is created on a separate block. The blocks are removable. So, you can customize your setup depending on what you want to measure.
The Bitalino EMG sensor is used to measure electrical activity that is produced by skeletal muscles. Many people don’t know this, but the movement of muscles is triggered by very small electrical currents in the body. By measuring and analyzing these currents, one can detect muscle fatigue, low back pain, disorders in motor control, activation level and the biomechanics of human movement.
Electrodermal activity (EDA) is also an important body characteristic that can be used in medical diagnosis and evaluation. It is the change in electrical properties of the skin, associated with sweat gland activity. Using the EDA sensor, one can identify different stimulus responses in the body and get relaxation biofeedback. It is useful in detection of changes in the emotional, cognitive and attentive states of the body.
If you want to measure the heat rate you will need the ECG sensor. It measures the electrical currents generated by the heart, via electrodes placed on the skin, and amplifies them. Some of the applications of the ECG sensor are heart rate and stress monitoring and monitoring whether a person is alive.
The accelerometer and LUX sensor are not specialized medical sensors, though they can be used in some biometric applications. For instance, the LUX sensor can be used together with a light source to monitor blood volume pulse data, while the accelerometer can be used in dynamic and biomechanical analysis of motion.
The Bitalino platform offers a simple and cheap way to acquire and analyze bio-signals. Through it, developers have managed to create biometrics-activated projects and applications that monitor health. It is also an affordable option for DIY enthusiasts who would like to create simple projects at home.
E-Health Sensor Platform
E-Health is an open-source sensor platform that offers a wide range of bio-signal sensing capabilities to open-source hardware platforms. It is one of the few, if not the only, health sensor shield that is compatible with both the Arduino and Raspberry Pi platforms. This makes it ideal for hardware development projects.
The E-Health shield supports up to 10 sensors. They include:
- Pulse sensor
- Oxygen in blood sensor
- Airflow sensor
- Body temperature sensor
- ECG sensor
- Galvanic Skin Response (GSR) sensor
- Blood pressure sensor
- EMG sensor
The ports and pins on the shield are designed specifically for the sensors listed above. All sensors are noninvasive and are designed with electrodes, clips and bands among several other features that make it easy to attach them safely onto the body. Using these sensors one can monitor the real-time state of a patient and be able to make a medical diagnosis.
Data that is collected from the patient can be stored remotely. This is done through Wi-Fi, Bluetooth, GPRS, 3G, ZigBee or 802.15.4 depending on the application. The data is always secure regardless of which mode of communication you use. This is because the platform has several security levels. The communication link layer has AES128 for ZigBee/802.15.4 and WPA2 for Wi-Fi, while the application layer uses HTTPS (secure) protocol. So, logged data is always secure.
It is also easy to visualize sensor data using the E-health shield. One can use a Graphic LCD (GLCD) screen to do so. Using the serial GLCD backpack, it is easy to display data received from the sensors via a simple serial interface. For real-time data viewing one can use KST, which is an open-source data logging software.
The Bitalino and E-health are fully fledged open-source healthcare platforms that can be used to provide elaborate medical diagnosis. However, if you want to integrate only one biometric sensor in your project, getting a standalone sensor would be more economical. There is a wide variety of such sensors available. So, you wouldn’t have a hard time getting them.
An Electrocardiography (ECG) device is used to measure the electrical activity of the heart. Almost all hospitals have ECG meters which are used to monitor heart activity of patients in critical conditions. If you haven’t seen one, you probably have heard it beep in a movie during a hospital scene.
There are several open-source ECG sensors that are available. They are not invasive and can be used from the comfort of one’s home. Their operation is based on different mechanisms. Photoplethysmography (PPG) is one of them.
PPG is a simple optical technique that is used to detect the changes in blood volume in the microvascular bed of tissue. PPG-based sensors measure the changes in blood volume in tissues using a light source and detector. Since variation in blood volume is directly proportional to the heart beat, this technique can be used to determine the heart rate. There are two types of PPG: transmittance and reflectance.
For a transmittance (PPG), a light source is shown directly onto the tissue and a light detector is placed on the other side of the tissue. The detector measures the amount of light that emerges on the other side of the tissue and uses its intensity to map the heartbeat. To understand more about transmittance PPG look at this DIY ECG project.
On the other hand, reflectance PPG relies on measurement of light that is reflected by tissue. The light source and the detector are usually on the same side of the body part. Light is shown onto the tissue and the detector receives the reflected light. A good example of an ECG sensor that uses this mechanism is the Arduino pulse sensor.
Arduino Pulse Sensor
Heart rate data can come in handy in many situations. It can be used to monitor health as well as automate some control systems and projects. A good example of such projects is an LED matrix that blinks to your heartbeat.
The pulse sensor is a plug-and-play heart rate sensor that can help you build such a project. It uses reflectance PPG principle to detect the heartbeat. It has all the sampling and amplification circuitry on board. Therefore, it only needs three wires to communicate with the microcontroller i.e. Vcc, Gnd and analog signal pin.
Using the pulse sensor is quite easy. All one needs to do is plug its pins into an Arduino board and run the example Arduino sketch that the manufacturers have provided. For a more detailed visualization of the heart rate, one can run the Processing java application that the manufacturers have also provided.
AD8232 Sparkfun Single Lead Heart Rate Monitor
If you are looking for a cheap alternative to the pulse sensor, then the AD8232 Sparkfun Single Lead Heart Rate Monitor is the sensor for you. Unlike the pulse sensor, it measures the electrical activity of the heart. The AD8232 amplifies the incoming signal so as to achieve a clear signal from the PR and QT intervals.
The AD8232, which is the core of the sensor module, is an integrated conditioning block for biometrics applications. It extracts biopotential signals, amplifies them and filters out any noise that emanates from movement of the electrodes. This leaves a clean signal that can be read by microcontrollers.
This sensor module has nine connections where pins or wires can be soldered onto. Some of the connections include SDN, LO+, LO-, OUTPUT, 3.3v, GND, RA, LA and RL. It also comes with sensor pads and a sensor cable which are used to get the electrical activity of the heart.
Polar Heart Rate Monitor Interface
The Polar heart rate monitor interface (HRMI) is a peripheral device that converts ECG signals from the Polar heart rate monitor into usable heart rate data. It does that using a complex algorithm that eliminates noise from the incoming signal. In addition to that, it has multiple interfaces, such as I2C, USB and Logic-level serial. Therefore, you can use it to communicate to different development boards including PCs.
The HRMI works with both coded and non-coded polar transmitters, such as T31, T61C, Wearlink and T31C. However, can only operate with one transmitter at a time. Moreover, the transmitter has to be in range in order to communicate with the HRMI. This device can be used in several equipment, like portable heart rate monitors, custom exercise equipment, heartbeat aware wearable electronics and bio-feedback devices.
NeuroSky MindWave Mobile
NeuroSky MindWave Mobile is an Electroencephalography (EEG) sensing headset that measures electrical activity along the scalp. The electrical activity is caused by voltage fluctuations that result from ionic current flows in the neurons of the brain. Data obtained from the sensor can be used to monitor the levels of relaxation and attention and enable one to know how the brain reacts to certain stimuli.
The MindWave Mobile has three main parts. They include a headset, sensor arm and ear clip. The reference and ground electrodes are located on the ear clip, while the EEG electrode is on the sensor arm, which rests on the forehead. The sensor uses Bluetooth to communicate wirelessly with computers, android devices and iOS devices. Therefore, all one needs to do is wear the sensor and monitor his or her brainwaves on a computer or smartphone.
You can use the MindWave in many different applications. This is because there are hundreds of educational apps, brain training games and development tools available on the Neurosky, Android and iOS stores. Moreover, you can write custom programs to interact with the sensor module using open-source developer tools.
MQ-3 Alcohol Gas Sensor
Just as its name suggests, the MQ-3 alcohol gas sensor is used to detect alcohol concentration in a person’s breath. It is the most important part of a breathalyser. The analog output of the sensor depends on the alcohol concentration in the breath of the subject and varies from 0 – 3.3v. The readings can be acquired using a simple ADC.
Muscle Sensor V3
Controlling projects using muscle movement is where technology is heading to. Not only will it eliminate the need for many input devices, but also increase the accuracy of input signals. Currently, this is possible using electromyography (EMG) sensors such as SparkFun’s Muscle Sensor V3.
This muscle sensor is similar to the Bitalino EMG sensor. It measures the filtered and rectified electrical activity of muscles and outputs 0 to Vs volts, where Vs is the voltage of the power source. The output voltage depends on the amount of activity in the muscles under observation. This sensor can be applied in different kinds of control systems that require biometric input.
There are many open-source healthcare platforms and sensors out there that you can use in your projects. However, the accuracy of their readings and their communication protocols might differ. Therefore, you have to make sure that the sensors you choose have the right resolution and can be interfaced with your development boards. With the right hardware, you will be able to get accurate biometric data for your projects.