ALI - Hack49 (1st mederr, 2nd overall, 3rd neuraltech)

Providing insights to dementia using speech analysis via an AI companion

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Inspiration Robot and Frank

Hack49 (1st place MedError, 2nd Overall, 3rd Neurotech) Velocity AgeTech ?

Welcome to Ali 🧠💬

What specific problem is your solution working to solve, how does it benefit the aging population?

The problem ALI is working to solve is the lack of a continuous, proactive approach to preventing cognitive decline in older adults. Many subtle, early signs of conditions like dementia are missed or dismissed as normal aging because current tests are often one-time, expensive, or invasive. This leads to delayed or inaccurate diagnoses, which in turn results in missed opportunities for early intervention that could significantly improve a person's quality of life.

The solution, a mobile app named ALI, benefits the aging population in two primary ways:

  1. Proactive Health Monitoring: The app uses AI to continuously listen to natural speech patterns throughout the day. By analyzing subtle changes in vocabulary and sentence structure, it creates a long-term, objective record of a person's cognitive health. This provides doctors and caregivers with better, ongoing data than traditional, one-time tests, enabling earlier and more accurate diagnoses.

  2. Enhanced Emotional Well-being: Beyond a diagnostic tool, ALI acts as a conversational companion to combat loneliness, a common problem for many older adults. It can also serve as a memory aid for daily tasks and encourage engagement in hobbies, promoting a sense of purpose. This dual approach helps improve both mental and emotional health.

For a look at how an AI companion can interact with older adults, check out this video. ElliQ: Your AI sidekick for happier, healthier aging

Why is your team best suited to solve this problem?

The team is best suited to solve this problem because of its deep understanding of both the technical and human aspects of eldercare, combined with a scalable, practical solution design.

  • The team has expertise in advanced AI technology like speech analysis for detecting early cognitive decline, ensuring Ali provides reliable, real-time health insights to caregivers and healthcare providers.

  • They have built Ali as a mobile application rather than requiring special hardware, which makes it highly accessible and easy to scale. Mobile devices are widely used by the current generation of older adults, particularly the "Baby Boomer" cohort (those born between 1946 and 1964), who are increasingly comfortable with digital technology and mobile apps. This demographic familiarity lowers barriers to adoption.

  • The team prioritizes seamless integration with existing care systems to improve workflows and caregiver efficiency, making Ali practical for large organizations serving diverse senior populations.

  • Their combined technical skills, user-focused design emphasis, and understanding of healthcare environments uniquely position them to develop a solution that is not only innovative but also implementable at scale with meaningful impact on aging care.

  • Furthermore, the team has actively engaged with partners and users to validate the solution’s usability, relevance, and scalability, meeting key judging criteria for real-world effectiveness and impact.

This combination of AI expertise, user accessibility, and thoughtful integration makes the team especially equipped to advance eldercare with a solution like Ali.The team is best suited to solve this problem because of its strong technical expertise in AI and speech analysis, deep understanding of eldercare challenges, and a focus on designing practical, scalable solutions. Ali is built as a mobile application, which is a major advantage because it does not require expensive or specialized hardware. The current generation of older adults, especially Baby Boomers (born 1946-1964), is increasingly comfortable using mobile devices, making Ali highly accessible to its target users. The team's approach emphasizes seamless integration with existing caregiving and healthcare systems, ensuring Ali fits naturally into current workflows. They have also engaged with potential users and partners to validate usability and effectiveness. This combination of innovation, accessibility, user insight, and real-world integration makes the team uniquely equipped to deliver impactful, scalable solutions in eldercare.

Here’s a clean list version of the judging criteria you provided:

Judging Criteria

  1. 📈 Impact and Relevance (25%)
  • Potential to positively improve the aging problem space.
  • Consideration of the impact on older adults or caregivers.
  • Alignment with the assigned problem spaces.
  1. ⚖️ Implementation and Scalability (25%)
  • Feasibility of real-world implementation.
  • Potential for integration with existing systems and processes.
  • Ability to scale for large organizations.
  • Evidence of feedback from relevant partners and users.
  1. 🖌️ Innovation and Creativity (25%)
  • Originality, innovation, and creativity of the solution.
  • Demonstrates a deep understanding of the problem.
  • Offers a unique approach to solving the assigned challenges.
  1. 📋 Presentation & Deliverables (25%)
  • Quality of the pitch and ability to communicate ideas effectively.
  • Clear, concise, and engaging presentation that conveys value and impact.

  • Showcase Breakdown:

    • 15%: Presentation and delivery.
    • 10%: Effort and display quality (trifold design, layout, content organization, and visual appeal).

Would you like me to also reformat this into a one-page judging sheet (like a rubric) for easier use during scoring?

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