boyle / 2018-measure-stress

Using machine learning to investigate sympathetic activation of the autonomic nervous system (SAANS) during the treatment of mild traumatic brain injury, chronic pain, and post-traumatic stress disorder.

Measure Stress

The project title is:

Using machine learning to investigate sympathetic activation of the autonomic nervous system (SAANS) during the treatment of mild traumatic brain injury, chronic pain, and post-traumatic stress disorder.

Summary

The goal of this research is to further our understanding and clinical management of Canadian Forces service members and veterans suffering from a complex medical triad of traumatic brain injury, chronic pain, and post-traumatic stress disorder. Over half of rehabilitation patients experience one or more of these complex medical conditions, often associated with intractable symptoms which do not respond to traditional treatment options, and impairing their ability to function effectively at work and in the community. Using a Computer Assisted Rehabilitation Environment (CAREN) this research will collect and consolidate a series of non-invasive whole- body biological measurements from patients during immersive therapy sessions in the CAREN Virtual Reality facility. High-performance computing and machine learning will be used to develop and deploy real-time estimators of SAANS. These systems will allow clinicians to create individualized treatment plans for patients, thereby maximizing rehabilitation benefits and avoiding costly setbacks in patient treatment.

Contributors and Partners

• Jim Green Principle Investigator
• Adrian Chan co-Principle Investigator
• Andrew Smith Post Doctoral Fellow
• Alistair Boyle Post Doctoral Fellow
• Roger Selzler Ph.D. Student
• Francois Charih Intern
• Dr. Jen McDonald The Ottawa Hospital Rehab Centre
• Janet Holly The Ottawa Hospital Rehab Centre
• L.Col Dr. Markus Besemann Canadian Forces, Health Services
• Col Dr. Rakesh Jetly Canadian Forces, Health Services
• Dr. Gaurav Gupta Canadian Forces, Health Services
• John Whitnall IBM

Repository Structure

The 'boot' directory contains the boot scripts to configure cloud compute resources from a bare Ubuntu 18.04 installation, to a functional appliance.

The 'www' directory contains the website which will be hosted on the public/internet facing side of the cloud environment. These pages will be publicly accessible. Pages should redirect to https for secure (SSL) connections. Private research group information should be password protected.

Remote Access from a Linux Host

From a linux host, you can get ssh access to the web server front-end using ssh <user>@saans.ca. To get to other servers in the system you can ssh via a "jump host" if you know the IP address of the local system ssh -J <user>@saans.ca <user>@<ip> for an internal <ip> address such as 172.16.59.9. You must have an account as <user> on the web server. If your username on your local computer matches that on the remote system you can drop the <user>@ portion of the command.

For example, to get to one of the compute nodes: ssh -J [e-mail] boyle@172.16.59.9

Similarly, one can get a graphical VNC session, by connecting through a competent VNC client such as TigerVNC: vncviewer -via [e-mail] 172.16.59.9:10 where the :10 is the VNC port number reported when you start a VNC server session vncserver from the command line. TigerVNC is available for windows machines as well: you will need to configure your SSH keys, but access will then work equally well from windows or linux.

SSH password authentication is disabled on all systems. You need an authentication key to login. See ssh-keygen and provide the public key (id_rsa.pub) to whomever is administering the servers.