IRIS

2021

UI/UX Design, Product Vision

Core 77 Design Award 2021
Who would’ve thought AI PIN came out 2 years later?

Blind/low-vision (BLV) occupational therapy helps patients adapt to their visions and aquire skills of activities of daily living (ADLs). However, occupational therapists can't be there for patients 24/7. Working with a BLV occupational therapist from the regional eye center, we designed IRIS for occupational therapists to generate and monitor patients' home exercises to reimagine BLV rehabilitation with the help of AI.

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Research - We conducted an observation of the full occupational therapy, and interviewed 3 stakeholders about their experiences in the BLV subject. While the clinic training is well-designed to teach patients essential skills, patients get frustrated when they apply them at home since training is not always applicable in real life. All interviewees emphasized customizability, low intrusion and real-life practices.

Product System - We proposed a system that fosters intelligent home exercises monitoring for both occupational therapists and BLV patients. Using cloud service, we connect OTs’ platform and patients’ wearable trackers to share information of home exercises seamlessly.

User Flow - Built upon the existing therapy paradigm, the new service system intends to create a positive feedback loop between the home exercise and clinic training sessions. It also fosters both synchronous and asynchronous feedback from OTs to patients.

The patient’s journey starts with the first appointment with the occupational therapist.

1. Evaluate Conditions - As usual, the occupational therapist first evaluates patients' conditions by asking questions, and the system will generate recommended home exercises based on the evaluation.

2. Customize Exercises - The OT and the patient will then select and customize home exercises together, choosing appropriate assistive devices, situational tips and other conditions to better assist patients.

3. Upload to cloud - Now that the activities are selected, OT uploads the exercises to Iris Cloud and hands the wearable camera to the patient to use it at home.

When the patient arrives home, they feel confident to start training exercises using Iris wearable AI coach.

4. Activate The Device - To start the exercise, the patient first monitor to see the tasks they are assigned. Once selected the exercise, the patient can clip the device to their head piece or their shirt, and press the start button to start exercising.

5.Assist Exercises - Using advanced image recognitiontechnology, the device can recognize objects, tasks, environments, and provide tips when performing corresponding tasks.

6. Upload Recordings - Once finishing with the assigned exercises, the exercise recordings and any audio feedback will be shared with their therapist.

Before the next appointment, OT opens the patient’s profile and reviews the exercise videos uploaded.

7. Review Home Exercise - Video recordings are timestamped automatically based on the steps of the exercises. The occupational therapist can annotate on the video timeline about patients' performance. When the patient arrives, they can review the videos and notes together and discuss the next trainings.

To progress from low-fi to mid-fi prototypes, we tested with OT Holly for concept validation. We also tested with peer designers from mid-fi to hi-fi to improve interface usability.