Quantifying Causes of Back Pain and Providing Individualized Recommendations

Develop a model that can quantify the various causes of back pain and make suitable individualistic training recommendations that can be followed in between short work breaks.

The problem

One of the most frequent causes of missed work or medical attention is back discomfort. The most common reason for incapacity in the world is back pain. Back discomfort can result from factors other than underlying diseases. Examples include overuse, such as excessive exercise or lifting, lengthy periods of sitting and lying down, poor sleeping positions, and carrying a heavy backpack. Injury, physical exercise, and various medical problems can also cause it. People of any age might have back discomfort for a variety of reasons. Fortunately, most back pain episodes may be prevented or treated, especially for those under the age of 60. In the case that prevention is unsuccessful, straightforward self-care and regular, proper exercise of the body will quickly cure the problem. Back pain is typically treated without surgery. With home therapy and self-care, the majority of back pain gradually gets better over the course of a few weeks. 

This Omdena-MinkTec project aims to quantify the causes of back pain and provide short, individualized training for every day, such as gamified mini-trainings in between 2-minute breaks at work.

The project goals

MinkTec’s sensor collects 18 highly accurate 3D coordinates along the spine and saves them in the cloud. At present, they are also doing a classification of activities of daily living (supervised and reinforced).

Project Scope:

• Partial data is available but need to do further augmentation
• Use deep learning to characterize daily activities and match them with the prevalence of back pain
• Develop a model that can determine and quantify the causes of back pain
• Create personalized recommendations in the form of gamified mini-trainings

Why join? The uniqueness of Omdena AI Innovation Challenges

A collaborative experience you never had in your working life! For the next eight weeks, you will not only build AI solutions to make a real-world impact but also go through an entire data science project lifecycle. This covers problem scoping, data collection, and preparation, as well as modeling for deployment.

And the best part is that you will join a global and collaborative team of changemakers. Omdena AI Challenges are not a competition or hackathon but a real-world project that will take your experience of what is possible through collaboration to a new level.

Find more information on how an Omdena project works