Introduction: Non-invasive Alzheimer's Light Therapy Devices

About: I am a junior at Jefferson Highschool in West Virginia, USA. I enjoy building various devices and I just recently started sharing my creations with the world.

This project is centered around the creation of devices aimed at being used in the study of the effects of Alzheimer's Light Therapy on humans. In December 2016, after publishing my first Instructable, Mr. Sotiris Melissis (graduate student at NYU) contacted me regarding a newly published article on a new Alzheimer's treatment method by MIT (http://news.mit.edu/2016/visual-stimulation-treatment-alzheimer-1207), he suggested that I build a device to aid in the testing of this therapy on humans. I agreed to create glasses with an LED that can cycle at 40Hz to help administer the light therapy to people as they walk, so that they do not have to stand in a test room to receive the therapy. Later a standalone room lamp that is capable of administering the therapy was also created and a remote with an OLED screen was also added to help the user control the two devices. In addition to the two devices being controllable via the remote, they can also be controlled through a phone or computer with wireless capabilities. The project uses ESP8266 12-E modules to achieve the wireless communication between the 3 core devices and since communication is achieved via Wi-Fi access points, they can also be connected to with a normal computer. Below are the three devices (glasses, standalone light, and remote)

Step 1: Parts List and Requirements

Step 2: Remote Circuitry

The first step to building these devices, was to assemble the remote circuit, which is comprised of an ESP, an OLED, and a couple of buttons.

When creating this circuit, one can either use solder to make the connections between the different pins of the components, jumper wires, or both. Follow the diagram to create the remote circuit. The battery can be tucked on the underside of the perfboard. The code running on this circuit creates a little menu on the OLED, where the user can control the light therapy lights and glasses. In order to navigate the menu, the user uses the 3 main buttons (topmost is to move up on the menu, middle is to confirm highlighted selection, bottom is to move down on the menu). The button on the far right of the circuit, is used to wake the ESP from sleep mode, the mode is used to conserve battery on the remote.

Step 3: Glasses Circuitry

After creating the remote circuit, the glasses circuit can be created. This is the easiest circuit to build as it has the least components. The ESP in this circuit is connected to an LED and that is essentially the entire circuit. The reason behind this circuit's simplicity, is that it is made to fit on the user's glasses, so it has to be small and light. A small Li-Po is used in order to fit on the glasses, and when placing the circuit on the glasses, the LED is placed in the corner of the lense on the glasses. The reason behind this placement is to provide light stimulus while also not being too distracting for the user.

Step 4: Standalone Light Circuitry

The final step to creating these interconnected devices, is the creation of the light/ lamp circuit. This circuit employs high power LEDs that the ESP cannot source the current for, so the [majority of the] power comes from the 3V 3A AC adapter. The PNP transistor exists to allow for high power switching (control) of the lights, by the ESP which receives commands from the remote. PLEASE MAKE SURE TO UNPLUG THE AC ADAPTER WHILE BUILDING THE CIRCUIT, AS THE HIGH POWER OUTPUT CAN KILL YOU. The red and black lines coming off of the circuit schematic connect to the anode and cathode of the AC adapter respectively.

Step 5: Programs and 3D Models

Programs Repository:

The remote, glasses, and standalone lamp are all using their own individual ESP modules and so they each have their own programs. The programs can be uploaded via the Arduino IDE, after downloading the 3 programs from the GitHub repository:https://github.com/Ultimatefire54/noninvasive-alz-...

After downloading the 3 programs, upload them to their respective ESP8266 circuit that you have already built.

3D Models:

Since there are 3 different devices/ circuits involved in this project, there are 3 different 3D models to act as cases for their respective circuits and provide an aesthetically pleasing look. The .STP files for the 3D models are provided below. .STP files are meant to be read by the printer only and cannot be edited using 3D modelling software, so download them when you are ready to print the cases.

Remote .STP:https://drive.google.com/open?id=0BwliXMzUsTp5eWZC...

Glasses .STP: https://drive.google.com/open?id=0BwliXMzUsTp5dlli...

Lamp .STP:https://drive.google.com/open?id=0BwliXMzUsTp5a1Bq...

Step 6: Light Therapy Testing

As mentioned before, this project is aimed at creating Alzheimer's Light Therapy devices that can be used to test the effectiveness of light therapy on humans. In the MIT paper published, the findings were that the light therapy inhibited the spread of Alzheimr's is mice's brains, so this is meant to test the therapy on humans. Mr. Sotiris Melissis is the graduate student who brought this idea to my knowledge and the one who will be conducting studies and testing the therapy on humans.

If you'd like to test the capabilities of this device, you may put on the glasses and initiate the therapy via the remote or stand in a room with the lamp which is also controlled through the remote. The brightness of the LED on the glasses can be varied through the remote for better comfort. A demonstration of controlling the glasses and lamp via the computer and remote is shown in the videos included with this section.

Step 7: About Me

My name is Adellar Irankunda and I am a junior at Jefferson high school in Jefferson County, West Virginia. If you need help completing this project or have any questions, please contact me at: addyirankunda@gmail.com.

Lights Contest 2017

Participated in the
Lights Contest 2017

Internet of Things Contest 2017

Participated in the
Internet of Things Contest 2017