The Artificial Light Texture (ALT) technology for non-contact vital signs (heartbeats, respiration) monitoring.

"A motion capture suite made out of light".

Quick links:

1. A Python script that can be used to capture and save infrared frames from the D400-series Intel RealSense cameras is available here. Additionally, a companion script that analyzes the metadata file generated by the frame capture script can be found here. The metadata file contains information about each captured frame, including its frame number and timestamp. The companion script identifies any gaps in the sequence of frame numbers (indicating dropped frames), calculates the effective frame rate (FPS), and provides a detailed report on frame continuity and performance. Instructions for these scripts are available here and here, respectively.

2. [GitHub] ALT technology based pulse and respiration monitoring using Intel RealSense cameras.

3. [LinkedIn, you need to be logged in] ALT technology based non-contact vital signs monitoring on mobile devices: an iPad + Structure Sensor example.

4. [Medium] Articles on Medium related to contactless sleep monitoring using ALT tech.

   A video (YouTube; Tip: set the video playback parameters to 1440p60 for this video for better video quality) from one of the articles on Medium showcasing the use of ALT tech for monitoring respiration during sleep. A screenshot from the video:

What is ALT?

The Artificial Light Texture (ALT) technology uses a video camera and a special light source to obtaining heart rate and respiration rate information for a person in a non-contact fashion and in real time.

Skin of the person does not have to be exposed to a video camera for ALT to work [1, 2, 3, 4]. ALT works for any pose of the person and even when the person is covered by a very thick blanket (or two) or wears loose-fiting clothes. ALT does not use depth data to obtain the vital signs information [1-4].

How does ALT work?

ALT can use inexpensive computing and image capture devices such as, e.g., Raspberry Pi single-board computer [5] and Pi NoIR camera [6] and is compatible with light emitting elements of various consumer electronics devices such as light projectors of standalone or embedded depth sensing devices like Microsoft Kinect ([7]; see below), Intel RealSense cameras [8-10], and Occipital Structure Sensor ([11]).

Three key hardware components of an ALT system are:

A computer, a video camera, and a light source which generates an artificial light texture.

The light source illuminates a set of areas of a person’s body thus imparting an additional (to the natural and/or artificial ambient light) light texture to a part of the person’s body. We call that additional light texture the “artificial light texture” or “ALT”. We call the distinct illumination areas of the added light texture its “elements”.

You can imagine the ALT as many light spots projected onto the person's body (as, e.g., shown above).

Application of the ALT can increase illumination contrast in the scene observed by a video camera. Movements of the person’s body which are related to the person’s respiration and/or heartbeats can lead to variations in one or more of the illumination distribution, shape distribution, size distribution, location distribution of the elements of the added light texture and/or to variations in the number of those elements, as observed by the camera.

These variations are captured by the video camera in a set of video frames which are processed by a computer to result in the numeric values representative of the heart rate and/or respiration rate of the person.

You can think about ALT as putting a person in a motion capture suite made out of light.

The added “artificial light texture” plays the role of an "amplification medium" for small body movements and its application to a person's body can lead to orders of magnitude increase in the ALT-signal components related to the heart activity and/or respiration of the person compared to the case when there is no “artificial light texture” (e.g. when the ALT-generating light emitter is switched off) and only the “natural light texture” is present during the otherwise equivalent data collection and processing procedure.

The ALT can cover parts of the objects which are in contact (direct or indirect) with the person’s body (e.g. a chair, a blanket, a bed, a floor, etc.) and movements or variations in the shape of such objects resulting from the movements of the person’s body imparted to them can be picked up in the ALT data too. This is why our ALT systems can detect heartbeats and respiration even when a person is completely hidden under a thick blanket [2].

An Exampl ALT system: Kinect + Raspberry Pi + Pi NoIR camera

In one implementation of the ALT technology that we will describe here, the light source element is the infrared light projector of a Microsoft Kinect for Xbox 360 system, the computing element is a Raspberry Pi single-board computer, and the video camera element is a Pi NoIR camera. Both the Kinect system and the Pi NoIR camera are connected to and controlled by the Raspberry Pi single-board computer.

ALT data that captures heartbeats and respiration of a person can be obtained by this system in the following way:

The infrared light projector of the Microsoft Kinect for Xbox 360 system illuminates a scene observed by the Pi NoIR camera;

Video encoding for the video frames captured by the Pi NoIR camera into H.264 format [12] is performed using the Raspberry Pi single-board computer and functionality provided by the Picamera library [13];

A set of the sum of absolute differences (SAD) values [14] is obtained for (ideally) each of the encoded video frames using the Raspberry Pi single-board computer and the Picamera library;

Further, a sum of the SAD values in the obtained SAD values set (the sSAD value) is calculated using the Raspberry Pi single-board computer for each of the encoded video frames for which the SAD values set was obtained.

Python code which runs on a Raspberry Pi single-board computer having a Pi NoIR camera connected to it and implements the video frames capture and processing steps described above can be found here. Microsoft Kinect can be connectd to and its emitter controlled by the same Raspberry Pi single-board computer.

The calculated sSAD values contain information about the respiration, heartbeats, and other movements of a person (e.g., movemens of arms, legs etc.) observed by the Pi NoIR camera over the time period covered by the encoded video frames. Numeric values representative of the respiration rate and/or heart rate of the person over that time period can be obtained, for example, by performing Fourier analysis [15] of the sSAD values.

Note that the ‘baseline’ of the sSAD values can be in the range of hundreds of thousands while the heartbeats/respiration/other movements signal can have just several percent amplitude relative to the ‘baseline’ even when the “artificial light texture” is applied to a person's body.

As a practical starting point, the Kinect system can be placed at approximately 5 feet distance from a person and the Pi NoIR camera can be placed in the vicinity of the Kinect. The distance between the Kinect/camera and the person can affect how pronounced the heartbeat signal will be during the respiration events (inhale/exhale sequence). Generally, the closer Kinect/camera gets to the person the less pronounced the heartbeat signal component in the ALT data becomes during respiration events. An example of the same effect for Intel RealSense cameras can be found here. Note also that at a large enough distance between the Kinect and the person there can be virtually no discernable pulse or respiration signal in the ALT data. Adjustments of the Kinect and the camera positions can be made, for example, based on observing visualizations of the collected ALT data.

An example of the ALT data captured by the embodiment of the ALT technology described above is shown in the figure below [1]. Real-time data collection was performed at 49 data points per second rate with simultaneous HD video (720p) recording. A person was at 1.5 meters (5 feet) distance from the camera. The camera observed 2/3 of the person's body. Determined rates are:

Respiration rate: 0.24 Hz or 14 respiration cycles per minute.

Heart rate: 1.12 Hz or 67 heartbeats per minute.

Although the ALT system described above can operate in virtually any lighting environment, an optical band pass filter which matches the wavelengths of the Kinect projector can be used with the Pi NoIR camera to reduce effects of fast (relative to the duration of a heartbeat or an inhale/exhale sequence) large-amplitude ambient light intensity variations such as the ones produced by incandescent light bulbs (at e.g. 60 Hz in the U.S.), especially if the incandescent light bulbs are the only source of light for a scene.

Implementations of the ALT technology components (hardware, software) other than the one described above habe been demonstrated. For example, we have shown that ALT systems can use Intel RealSense cameras which generate both static (R200 [9], D415 [16], D435 [16]) and dynamic (F200 [10]) light patterns [4]. The ALT technology can use light source elements which emit light on different wavelengths either visible or invisible to a human eye, depending on the needs of a particular application.

Qestions? Comments?: info(at)lvetechnologies.com; https://lvetechnologies.com/

Tip jar: bc1qg7j26tlw60mtt9vsczu6rzxlvuyql78a0xf3pr (BTC)

PS: Making heartbeats audible using ALT tech (YouTube video)

References (NOTE: some links can become outdated):

1. “Non-contact real-time monitoring of heart and respiration rates using Artificial Light Texture" https://www.linkedin.com/pulse/use-artificial-light-texture-non-contact-real-time-heart-misharin

2. “What has happened while we slept?" https://www.linkedin.com/pulse/what-has-happened-while-we-slept-alexander-misharin

3. “When your heart beats” https://www.linkedin.com/pulse/when-your-heart-beats-alexander-misharin

4. “ALT pulse and respiration monitoring using Intel RealSense cameras" https://www.linkedin.com/pulse/alt-pulse-respiration-monitoring-using-intel-cameras-misharin

5. https://www.raspberrypi.org/

6. https://www.raspberrypi.org/products/pi-noir-camera-v2/

7. “Kinect” https://en.wikipedia.org/wiki/Kinect

8. http://www.intel.com/content/www/us/en/architecture-and-technology/realsense-overview.html

9. “Introducing the Intel® RealSenseTM R200 Camera (world facing)” https://software.intel.com/en-us/articles/realsense-r200-camera

10. “Can Your Webcam Do This? - Exploring the Intel® RealSenseTM 3D Camera (F200)” https://software.intel.com/en-us/blogs/2015/01/26/can-your-webcam-do-this

11. “3D scanning, augmented reality, and more for mobile devices”, https://structure.io

12. "H.264/MPEG-4 AVC" https://en.wikipedia.org/wiki/H.264/MPEG-4_AVC

13. http://picamera.readthedocs.io

14. "Sum of absolute differences" https://en.wikipedia.org/wiki/Sum_of_absolute_differences

15. “Short-time Fourier transform” https://en.wikipedia.org/wiki/Short-time_Fourier_transform

16. https://realsense.intel.com/stereo/

ALT by Alexander Misharin, LVE Technologies LLC is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The full text of the CC BY-NC-SA 4.0 license can be found at https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode. Contact LVE Technologies LLC if you would like to obtain a commercial license: info(at)lvetechnologies.com