Jind CPR - D.H.C.A: First-Aid

Each year, roughly 1800 New Zealanders suffer cardiac arrest within community settings, and a scant 10% of them survive beyond 30 days. Immediate bystander intervention, such as the initiation of CPR and deployment of an AED within the critical initial minutes of cardiac arrest, can dramatically increase the patient's odds of survival. However, every passing minute without CPR or AED use reduces the patient's survival likelihood by 10-15%.

A meager 4.4% of New Zealand's population is qualified to administer First Aid. What's more, even those trained have reported difficulties in recalling the required steps amidst high-pressure scenarios, largely due to the intricate nature of the First Aid guide.

In response to this issue, we have developed Jind, a Digital Human-like Conversational Avatar (DHCA), offering a ground-breaking approach to First-Aid instruction. Jind can offer detailed rundowns of medical procedures integral to First Aid, rendered accessible whenever needed. The avatar's human-like interaction fosters a more authentic and engaging experience.

The application transcends mere conversational guidance by incorporating a simplified manual walkthrough for performing CPR. Jind's dialogue is rooted in the NZ Red Cross Essential First-Aid Manual, while her attire echoes the uniforms donned by St. John First-Aid respondents. The name 'Jind' was selected due to its translation to 'life' in Punjabi.

While Jind is currently a prototype offering solely CPR guidance, future enhancements plan to extend her scope to cover as many sections of the First-Aid guide as feasible.

Please bear in mind that this content is provided for informational and educational purposes exclusively, and we make no claims or guarantees regarding the accuracy, applicability, fitness, or completeness of the content. The content is not meant to replace professional medical advice, diagnosis, or treatment. We absolve ourselves of any liability to any party for any direct, indirect, implied, punitive, special, incidental, or other consequential damages deriving directly or indirectly from the usage of the content.

Rawinder Singh

rawinder457@gmail.com

https://github.com/lilwindax

Acknowledgements:

Devon Gibson (3D Modeling), Scott Hwang (Proj F)