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The Honda Walking Assist Device is a robotic exoskeleton that fits orthotically on the user's waist and thigh, outside of clothing. The device is intended to help assist ambulatory function in rehabilitation institutes under the supervision of a trained healthcare professional for the following population:

• Individuals with stroke who have gait deficits and exhibit gait speeds of at least 0.4m/s and are able to walk at least 10 meters with assistance from a maximum of one person.
  The trained healthcare professional must successfully complete a training program prior to use of the device. The devices are not intended for sports.

The Honda Walking Assist Device is a lightweight, robotic exoskeleton designed to help assist ambulatory function of stoke patients who meet the user assessment criteria, in rehabilitation institutes under the supervision of a trained healthcare professional. The device is worn around the user's waist and thighs, and assists with hip ioint flexion and extension. The device weighs 5.95lbs and has two motors that run on a single rechargeable battery. The device is equipped with angle and current sensors to monitor hip joint angle and torque output respectively. The assist torque is transmitted to the user's thighs via thigh frames. A trained healthcare professional, who operates the device, can change assist settings through software that runs on a mobile device.

The provided text details the 510(k) premarket notification for the Honda Walking Assist Device, a robotic exoskeleton. This document primarily focuses on demonstrating substantial equivalence to a predicate device (Ekso Bionics® Ekso) rather than presenting a traditional acceptance criteria table with performance metrics for an AI medical device.

The study described is a clinical effectiveness study of the device itself, not a study proving an AI algorithm meets specific acceptance criteria in terms of diagnostic performance (e.g., sensitivity, specificity). Therefore, the direct answers to some of your prompt's questions related to AI-specific evaluation (like ground truth establishment for AI training/test sets, MRMC studies, or standalone algorithm performance) are not explicitly present in the provided text, as this is a physical medical device clearance, not an AI algorithm clearance.

However, I can extract the relevant information from the document regarding the clinical study and the device's performance that supports its clearance.

Device: Honda Walking Assist Device

Acceptance Criteria and Reported Device Performance

As this is a physical medical device clearance and not an AI algorithm, specific "acceptance criteria" for metrics like sensitivity, specificity, or AUC as one would expect for an AI diagnostic device are not detailed. Instead, the "acceptance" hinges on demonstrating safety and effectiveness comparable to a predicate device, and improvement in a clinical outcome.

The primary endpoint for demonstrating effectiveness was the change in 10 Meter Walk Test (MWT) Self-selected Velocity (SSV) from baseline in gait speed.

Study Details:

1. Sample size used for the test set and the data provenance:

   • Test Set (Clinical Study): 50 participants total.
     • Honda Walking Assist (HWA) Group: 25 participants
     • Functional Task Specific Training (FTST) (Control) Group: 25 participants
   • Data Provenance: The study was conducted at The Shirley Ryan AbilityLab (Chicago, Illinois, USA). It was a randomized controlled trial. The data appears to be prospective as it describes a clinical trial.

2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

   • This is a clinical effectiveness study of a physical device, not an AI algorithm evaluating medical images or data where "ground truth" is established by experts in the diagnostic sense.
   • The "ground truth" for assessing device effectiveness is the objective measurement of gait speed using the 10 Meter Walk Test (MWT) Self-selected Velocity (SSV), which is a standard clinical assessment. The study was conducted "under the supervision of a trained healthcare professional." While not explicitly stated how many conducted the MWT measurements, it would be standard practice for trained healthcare professionals (e.g., physical therapists) to perform these assessments. The document emphasizes that "The trained healthcare professional must successfully complete a training program prior to use of the device" and that the study was conducted "under clinical supervision."

3. Adjudication method for the test set:

   • Not applicable in the context of this study. The primary endpoint (gait speed) is an objective measurement rather than a subjective assessment requiring adjudication.

4. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

   • No, an MRMC study was not done. This study evaluated the direct impact of the robotic exoskeleton on patient gait, not the performance of an AI algorithm assisting human readers.

5. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

   • No, this question is not applicable. The device itself (exoskeleton) operates with a human in the loop (the patient wearing it, supervised by a healthcare professional). The document describes software on a mobile device used by the healthcare professional to change assist settings, but this isn't presented as an AI algorithm with standalone diagnostic performance.

6. The type of ground truth used:

   • The "ground truth" for evaluating the device's effectiveness was objective clinical measurement outcomes, specifically the change in 10 Meter Walk Test, Self-selected Velocity (SSV). Safety was assessed by monitoring and reporting adverse events, including falls.

7. The sample size for the training set:

   • This question typically refers to the dataset used to train an AI algorithm. The provided text does not mention a separate "training set" in the context of an AI algorithm.
   • For the device's clinical validation, the "training" refers to the intervention itself:
     • 18 total training sessions for both groups (HWA and FTST).
     • Each session was 45 minutes, 3 sessions/week, over 6-8 weeks.

8. How the ground truth for the training set was established:

   • Not applicable as there is no AI algorithm training set described. The "training" for the device involved patients undergoing gait and stair training exercises facilitated by the device. Effectiveness was measured by the change in the 10 Meter Walk Test, as described above.

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