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The EksoNR™ is intended to perform ambulatory functions in rehabilitations under the supervision of a trained physical therapist for the following populations:

· Individuals with multiple sclerosis (upper extremity motor function of at least one arm).

• Individuals with acquired brain injury, including traumatic brain injury and stroke (upper extremity motor function of at least 4/5 in at least one arm).

· Individuals with spinal cord injuries at levels T4 to L5 (upper extremity motor function of at least 4/5 in both arms).

· Individuals with spinal cord injuries at levels of C7 to T3 (ASIA D with upper extremity motor function of at least 4/5 in both arms).

The therapist must complete a training program prior to use of the devices are not intended for sports or stair climbing

The Ekso is a powered motorized orthosis. It consists of a fitted metal brace that supports the legs, feet, and torso. It is worn via straps on the body, legs, and feet. Battery powered motors drive knee and hip joints. It has an integrated solid torso containing the computer and power supply. It has a hand-held user interface to specify settings and initiate steps. The Ekso is used with a cane, crutch, or walker.

Here's an analysis of the provided text, extracting information related to acceptance criteria and the study proving the device meets them. Please note that the document is a 510(k) summary for a medical device (exoskeleton), which focuses on demonstrating substantial equivalence to a predicate device rather than presenting a formal "acceptance criteria" table as might be seen for an AI/ML diagnostic tool. Therefore, some requested information may not be directly available or applicable in the provided context.

Overview:
The document clears the EksoNR powered lower extremity exoskeleton. The primary purpose of this 510(k) submission (K220988) is to expand the indications for use of the already cleared EksoNR (predicate device K200574) to include individuals with multiple sclerosis (MS). The device itself is essentially unchanged from the predicate.

Acceptance Criteria and Device Performance

Given this is a 510(k) for an updated indication for an existing medical device (exoskeleton) rather than an AI/ML diagnostic, the concept of "acceptance criteria" isn't framed as statistical thresholds for sensitivity/specificity. Instead, the acceptance criteria are implicitly that the device is safe and effective for the expanded population, demonstrating gait ambulation effectiveness and no new safety concerns in the specified population, thus maintaining substantial equivalence to the predicate.

Table of Acceptance Criteria (Implicit) and Reported Device Performance:

• TUG scores improved significantly: from 24s at baseline to 20.61s at completion of all Ekso sessions.
• Average walking speed maintained: from 0.69m/s at baseline to 0.66m/s at completion of all Ekso sessions.
• Average cognitive MOCA scores improved slightly.

Kessler MS Study (n=8):

• TUG scores improved significantly: from 16.99s at baseline to 14.15s at completion of all Ekso sessions.
• Average walking speed maintained: from 10.37s at baseline to 10.63s at completion of all Ekso sessions (note: units here are stated as 's' which is unusual for speed, likely a typo and referring to time for a specific distance or a different test. See 6MWT below).
• Symbol digit modalities test (cognition) improved.
• 6 minute walk test (6MWT) distance increased: from 279.65m to 294.69m.
• Average functional reach test distance increased.

Overall Conclusion: "The supporting clinical data demonstrating the use of the product with patients with multiple sclerosis (MS), show that the device effectively facilitates gait ambulation in the expanded patient population." |
| Substantial Equivalence: Device remains substantially equivalent to the predicate (K200574). | "This device and the previously cleared (predicate) device (K200574) are essentially the same products."
"The device is essentially unchanged from the current (predicate) device."
"The indications for use are identical to that of the predicate device, with the addition of the following: Individuals with multiple sclerosis..."
"When used as instructed, the device is as safe to use with a broader population of patients with neurological conditions to include the already cleared ABI and SCI population and this new MS population." |

Study Details

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

   • Test Sets:
     • ADEMBI MS Study: 18 subjects total used the Ekso. (n=17 for TUG post-testing, n=18 for others).
     • Kessler MS Study: 9 subjects total used the Ekso. (n=8 for pre/post testing).
   • Data Provenance: Not explicitly stated regarding country of origin, but described as "Single center, prospective parallel-assignment, single-blinded, randomized controlled study" for ADEMBI MS and "Single center, randomized study" for Kessler MS. This implies prospective data collection for these specific studies. No specific mention of retrospective vs. prospective is made for the original 7 studies that supported the predicate.

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

   • This is not an AI/ML diagnostic device where ground truth is established by expert readers interpreting images or data. For an exoskeleton, the "ground truth" for effectiveness is whether the patient can ambulate and improve functional scores, as measured by standardized clinical tests (TUG, 6MWT), and the "ground truth" for safety is the absence of adverse events/falls during supervised use.
   • The device is used under the supervision of a "trained physical therapist." While not "experts establishing ground truth" in the diagnostic sense, their training and supervision are crucial for the device's safe and effective use and thus for the clinical outcomes.

3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

   • Not applicable. This is a functional device study, not an imaging diagnostic study requiring adjudication of image interpretations for ground truth. Clinical outcomes were measured directly using standardized tests and adverse events were reported.

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:

   • Not applicable. This is not an AI-assisted diagnostic tool. No MRMC study was performed or needed. The device (EksoNR) is the primary intervention.

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

   • Not applicable. The device is a physical exoskeleton designed for human-in-the-loop use under therapist supervision. It does not operate as a standalone algorithm.

6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

   • Outcomes Data: The primary ground truth is established through measured clinical outcomes using validated functional assessment tools (e.g., Timed Up and Go (TUG) test, 6-minute walk test (6MWT), cognitive assessments like MOCA/Symbol Digit Modalities Test) and direct observation/reporting of adverse events (falls). This is outcomes-based evidence of safety and functional improvement.

7. The sample size for the training set:

   • Not applicable in the context of device approval for an exoskeleton. This is not an AI/ML algorithm that requires a "training set" in the computational sense. The device itself is "trained" during the manufacturing and design process, and the physical therapists are trained for its use.

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

   • Not applicable. As above, there is no AI/ML "training set" for this device. The physical therapists are trained users, and their "ground truth" would be established through their professional education, experience, and the specific training program provided for the EksoNR device.

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The EksoNR™ is intended to perform ambulatory functions in rehabilitations under the supervision of a trained physical therapist for the following populations:

• · Individuals with acquired brain injury, including traumatic brain injury and stroke (upper extremity motor function of at least 4/5 in at least one arm).
• · Individuals with spinal cord injuries at levels T4 to L5 (upper extremity motor function of at least 4/5 in both arms).
• · Individuals with spinal cord injuries at levels of C7 to T3 (ASIA D with upper extremity motor function of at least 4/5 in both arms).
  The therapist must complete a training program prior to use of the devices are not intended for sports or star climbing.

The Ekso is a powered motorized orthosis. It consists of a fitted metal brace that supports the legs, feet, and torso. It is worn via straps on the body, legs, and feet. Battery powered motors drive knee and hip joints. It has an integrated solid torso containing the computer and power supply. It has a hand-held user interface to specify settings and initiate steps. The Ekso is used with a cane, crutch, or walker.

The provided text is a 510(k) Summary for the EksoNR™ exoskeleton, a medical device for rehabilitation. It details the device's indications for use, its technical characteristics, and non-clinical and clinical performance data to support its substantial equivalence to a predicate device.

However, the information provided does not contain details about an AI/algorithm-driven device, nor does it specify acceptance criteria in terms of quantitative performance metrics (like sensitivity, specificity, or AUC) that would be typically found for such a device. The document focuses on showing the device's safety and effectiveness for an expanded patient population in rehabilitation based on clinical studies, rather than the performance of an algorithm.

Therefore, I cannot extract the information required to populate the requested table or answer questions related to AI/algorithm performance, ground truth establishment for a test set, expert adjudication, or MRMC studies.

The document indicates "Software - Verification, Validation, and hazard analysis" was performed, but it does not describe a study involving a test set, ground truth experts, or performance metrics relevant to an AI/algorithm's diagnostic or predictive capabilities. It primarily discusses the exoskeleton's performance in facilitating gait ambulation and safety for patients, not an AI's performance in, for example, image analysis or diagnostic prediction.

To answer your request thoroughly, I would need a document describing an AI/algorithm-driven medical device and its performance evaluation against defined acceptance criteria.

Ask a specific question about this device