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The Indego® orthotically fits to the lower limbs and the trunk; the device is intended to enable individuals with spinal cord injury at levels T3 to L5 to perform ambulatory functions with supervision of a specially trained companion in accordance with the user assessment and training certification program. The device is also intended to enable individuals with spinal cord injury at levels C7 to L5 to perform ambulatory functions in rehabilitations in accordance with the user assessment and training certification program. Finally, the Indego® is also intended to enable individuals with hemiplegia (with motor function of 4/5 in at least one upper extremity) due to cerebrovascular accident (CVA) to perform ambulatory functions in rehabilitations in accordance with the user assessment and training certification program. The Indego is not intended for sports or stair climbing.

Parker Hannifin's Indego® device is a wearable powered exoskeleton that actively assists individuals to stand and walk; these are patients with walking impairments resulting from lower extremity weakness or paralysis. The Indego consists of snap-together components weighing 26 pounds total. The hip component houses a rechargeable battery pack, central processor, and Bluetooth radio, while each upper leg component houses two motors as well as embedded sensors and controllers.

In the original operational mode of the device, called Motion+, on-board microprocessors receive signals from integrated sensors which provide information on the user's posture and tilt. This allows the device to function in a manner similar to the Segway personal mobility device, which is controlled by the user's tilt. A user similarly controls the motions of the Indego by means of postural changes (e.g., to walk forward, the user just leans forward). Alternatively, the device can be placed in a second operating mode, referred to as Therapy+, in which the device responds to the motion of users who are able to initiate stepping on their own. When operating in Therapy+, the user walks normally while the system detects step initiation and assists the user. Therapy+ may be used only in a clinical setting under clinical supervision. The technology of the design links the low profile to advanced battery technology (smaller size), motors (smaller and more powerful), and micro controllers (state-of-the art). Visual cues from the LED lights on the hip and vibratory feedback inform both the patient and therapist or trained support person of the status and mode of operation.

The Indego controls are self-contained, with crutches or a walker used solely for stability. Users can perform sit-to-stand and stand-to-sit transitions and walk along even or uneven terrain up to about five degree (5°) grades. Tall hip wings and a tall torso pad are provided to support users who may need additional trunk support while walking. A physical therapist can configure, operate, and monitor the device during therapy and training to make adjustments as needed. This is achieved through the support of a wireless application that will run on mobile/wifi connected smart devices such as an iPod or iPhone. The patient and physical therapist will be able to work in concert to actions of transitioning from sitting to standing to walking, stop walking, and return from standing to sitting. The untethered, free-roaming design of the device allows it to be utilized in multiple indoor and outdoor locations within a rehabilitation or personal setting.

The provided text is a 510(k) Premarket Notification for the Indego® powered lower extremity exoskeleton. It details the device's indications for use, its description, and its comparison to predicate devices, along with non-clinical and clinical performance data.

However, the document does not contain typical "acceptance criteria" and "reported device performance" in the format of a table with specific metrics for an AI/ML powered device. Instead, the document focuses on demonstrating substantial equivalence to predicate devices through various tests and clinical studies for a physical medical device (an exoskeleton).

Therefore, I cannot directly provide a table of acceptance criteria and reported device performance as if it were an AI/ML algorithm being validated. The performance metrics discussed are for the physical functionality and safety of the exoskeleton, not for an algorithmic output.

Similarly, the information requested regarding "sample size for the test set," "data provenance (e.g. country of origin of the data, retrospective or prospective)," "number of experts used to establish the ground truth," "adjudication method," "MRMC study," "standalone performance," "type of ground truth," "sample size for the training set," and "how the ground truth for the training set was established" are all highly relevant to the clinical validation of AI/ML algorithms. This document does not describe an AI/ML algorithm for which these questions would apply in the traditional sense. The "software verification and validation testing per FDA Guidance and IEC 62304" mentioned in section 9 refers to software for controlling the physical device, not an AI for diagnostic or prognostic purposes.

Based on the provided text, here's what can be extracted and inferred regarding the closest relevant information, keeping in mind the context of a physical exoskeleton, not an AI/ML algorithm:

No direct "acceptance criteria" table for an AI/ML device can be constructed as this document is for a physical medical device (exoskeleton) and does not describe an AI/ML algorithm's performance.

The document does describe various non-clinical and clinical tests to demonstrate the safety and effectiveness of the Indego® exoskeleton. The "acceptance criteria" would be implied by the "PASS" status for non-clinical tests and the positive outcomes of the clinical studies.

Here's an attempt to adapt the requested information based on the provided text, while acknowledging its original context:

1. Table of Acceptance Criteria and Reported Device Performance (Adapted for Exoskeleton Functionality):

2. Sample Size and Data Provenance for Test Set:

• Test Set (Clinical Trials):
  • Main Multisite Clinical Trial: 30 subjects
  • Single-Site Pilot Study 1: 3 subjects
  • Single-Site Pilot Study 2: 3 subjects
  • Engineering Study: 6 subjects (ongoing)
  • Total unique subjects across all clinical studies: 42 individuals with CVA.
• Data Provenance: The documents mention "eight clinical sites" for the main multisite trial but do not specify countries of origin other than "Shepherd Center (Atlanta, GA)" for the engineering study. The studies appear to be prospective clinical trials evaluating the device in use.

3. Number of Experts and Qualifications for Ground Truth:

• This section is not directly applicable in the AI/ML sense of establishing a "ground truth" for input data. The "ground truth" for the exoskeleton is the direct, observable performance of the device and the physiological responses of the users.
• Clinical data collection and assessments involved "physical therapists" and "specially trained companion(s)" who supervised and assessed the users. Their specific qualifications (e.g., years of experience, board certification) are not detailed but are implied by their roles in a clinical setting.
• The "IRB approved" and "Good Clinical Practice (GCP) compliant" nature of the studies indicates adherence to ethical and scientific standards in clinical research.

4. Adjudication Method for the Test Set:

• Not applicable in the context of AI/ML ground truth adjudication. Clinical trial data collection involves various assessments by clinicians. The document does not describe a formal multi-reader adjudication process for qualitative assessments but rather direct measurement and observation of physical outcomes by trained personnel.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

• No, a MRMC study (typical for diagnostic or prognostic AI) was not done.
• The clinical studies focus on the device's ability to facilitate ambulatory functions and improve gait parameters in individuals with neurological impairments (SCI, CVA). There is no comparison of human readers with vs. without AI assistance. The "assistance" itself is the physical exoskeleton.

6. Standalone Performance (Algorithm Only):

• Not applicable. The "device" is a physical exoskeleton designed for human-in-the-loop operation. Its performance is measured in conjunction with a user, not as a standalone algorithm. The "software" component controls the physical device's functions.

7. Type of Ground Truth Used:

• The "ground truth" is derived from directly observable functional performance and physiological measurements during use of the physical device by human subjects. This includes:
  • Functional Outcomes: Ability to sit, stand, walk, turn; walking speed (10MWT); Functional Ambulation Classification (FAC) scores.
  • Physiological/Gait Parameters: Gait deviations, step length, stride length.
  • Safety Data: Incidence of adverse events.
  • Expert Observation/Assessment: Assessments by physical therapists and trained companions.

8. Sample Size for the Training Set:

• Not applicable as this is not an AI/ML algorithm in the context typically discussed for "training sets." The device undergoes extensive non-clinical testing and clinical evaluation.
• The document implies iterative design and testing for the physical device and its control software. For instance, the improvement in stand-to-sit transition after an adverse event suggests design modification based on observational data, akin to development cycles rather than a distinct "training set" for an AI model.

9. How the Ground Truth for the Training Set was Established:

• Not applicable for the same reasons as #8. The "training" here refers to device development and improvement, not algorithmic learning. System functionality and safety are established through engineering design principles, non-clinical validation (e.g., torque, durability, battery life tests), and iterative clinical testing.

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The Indego® orthotically fits to the lower limbs and the trunk; the device is intended to enable individuals with spinal cord injury at levels T3 to L5 to perform ambulatory functions with supervision of a specially trained companion in accordance with the user assessment and training certification program. The device is also intended to enable individuals with spinal cord injury at levels C7 to L5 to perform ambulatory functions in rehabilitations in accordance with the user assessment and training certification program. The Indego is not intended for sports or stair climbing.

Parker Hannifin's Indego® device is a wearable powered exoskeleton that actively assists individuals to stand and walk; these are patients with walking impairments resulting from lower extremity weakness or paralysis. The Indego consists of snap-together components weighing 26 pounds total. The hip component houses a rechargeable battery pack, central processor, and Bluetooth radio, while each upper leg component houses two motors as well as embedded sensors and controllers. On-board microprocessors receive signals from integrated sensors which provide information on the user's posture and tilt. This allows the device to function in a manner similar to the Segway personal mobility device, which is controlled by the user's tilt. A user similarly controls of the Indego by means of postural changes (e.g., to walk forward, the user just leans forward). The technology of the design links the low weight and low profile to advanced battery technology (smaller size), motors (smaller and more powerful), and micro controllers (state-of-the art). Visual cues from the LED lights on the hip and vibratory feedback inform both the patient and therapist or trained support person of the status and mode of operation. The Indego controls are self-contained, with forearm crutches or a walker used solely for stability. Users can perform sit-to-stand and stand-to-sit transitions and walk along even or uneven terrain up to about five degree (5°) grades. Taller torso "wings" are provided to support users who may need additional trunk support while walking. A physical therapist can configure, operate, and monitor the device during therapy and training to make adjustments as needed. This is achieved through the support of a wireless application that will run on mobile/wifi connected smart devices such as an iPod or iPhone. The patient and physical therapist will be able to work in concert to achieve the actions of transitioning from sitting to standing, standing to walking, stop walking, and return from standing to sitting. The untethered, free roaming design of the device will allow it to be utilized in multiple indoor and outdoor locations in either a rehabilitation setting with a certified Indego Specialist or a personal setting with a trained support person.

The provided text describes the Indego® powered lower extremity exoskeleton, and its substantial equivalence submission (K171334) to the FDA. The submission emphasizes clinical and non-clinical data to support expanded indications for use.

Here's an analysis of the acceptance criteria and the study proving the device meets these criteria, based on the provided text:

Key Takeaway: The device's "acceptance criteria" are not explicitly defined as specific numerical thresholds for performance metrics to achieve FDA clearance in the same way clinical trials for pharmaceuticals might state primary endpoints. Instead, the "acceptance criteria" are implicitly demonstrated by showing the device's safety and effectiveness for its intended use, comparable performance to predicate devices, and successful completion of various non-clinical and clinical tests. The primary measure of clinical success appears to be enabling ambulatory functions with minimal assistance (FIM score of 4 or higher) and demonstrating walking speed.

1. Table of Acceptance Criteria and Reported Device Performance

Since explicit acceptance criteria with numerical targets are not stated, the table below will summarize the demonstrated performance and implicitly infer the "acceptance criteria" based on the successful clearance. The core "acceptance criterion" appears to be demonstrating safety and effectiveness for the stated Indications for Use, with performance comparable or better than predicate devices.

2. Sample Size Used for the Test Set and Data Provenance

The terms "test set" and "training set" are typically used in machine learning. However, for medical device clinical studies, we can interpret the clinical data used for evaluation (which serves a similar purpose to a "test set" in demonstrating performance) as follows:

• Pilot Study: 16 subjects
• Multi-Site Clinical Trial: 45 subjects
• Postmarket Clinical Data (Rehabilitation Use): 37 subjects
• Personal Use Training Program Study: 4 subjects (user and support person teams)
• Postmarket Personal Use Data: 5 subjects (user and support person teams)

Total unique subjects across all reported clinical studies: While there might be some overlap, the text states "TOTAL SCI SUBJECTS: 107" for Indego data (comparing to Ekso's 56). This suggests the aggregate number of unique individuals whose data contributed to the clinical evaluation is 107.

Data Provenance:

• The text doesn't explicitly state the country of origin for all clinical data. However, the contact information for the sponsor (Parker Hannifin) is in USA (Ohio), and the submission correspondent (Emergo) is in USA (Texas). The postmarket personal use data mentions "5 trained Indego personal users worldwide. One of these individuals is a European user... The other 4 are from the United States." This indicates a mix of US and implied international data for personal use.
• The studies were prospective in nature, as they describe "Pilot Study", "Multi-Site Clinical Trial", and "Personal Use Training Program Study" which were IRB-approved and conducted according to GCP. Postmarket data would be collected retrospectively from existing users.

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This device is not an AI/ML diagnostic tool, so the concept of "ground truth" derived from expert consensus (e.g., radiologists interpreting images) isn't directly applicable in the same way.

Instead, for this exoskeleton device, "ground truth" or clinical outcomes are established through:

• Direct observation and measurement by trained clinical personnel (e.g., physical therapists, study coordinators) conducting the tests (10 MWT, 6 MWT, TUG, WISCI, FIM scores).
• Patient self-report/feedback for aspects like ease of use and satisfaction with training.
• Physician assessment for patient suitability and injury levels.

The qualifications of the personnel involved are implied by references to "specially trained companion", "physical therapist," "Indego Specialist," and "clinicians." The training and certification programs for both clinicians and personal users (with support persons) indicate a standardized approach to application and performance assessment. No specific number of "experts" for a consensus ground truth committee is mentioned, as the data collection methods are objective measurement and direct clinical observation.

4. Adjudication Method for the Test Set

Given that this is a physical therapy/mobility device study, and not an image-based diagnostic study where multiple readers might interpret findings, a formal "adjudication method" like "2+1" or "3+1" (common for reconciling discordant image interpretations) is not applicable here. Performance measures (e.g., walking speed, distance, FIM scores) are objective and directly measured or scored by the trained clinical staff involved in the studies. Adverse events are recorded and investigated as part of standard clinical trial procedures.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done.

MRMC studies are typically used to evaluate the impact of a diagnostic tool (like an AI algorithm) on human reader performance, usually in radiology, by comparing diagnostic accuracy or efficiency with and without AI assistance across multiple cases and readers. This exoskeleton is a treatment/assistive device, not a diagnostic one.

The studies focused on the device's standalone performance and safety in enabling mobility for individuals with SCI, rather than assisting human readers in interpreting data. The "assistance" refers to the device assisting the patient, not AI assisting a human healthcare provider's diagnostic process.

6. Standalone Performance (i.e. algorithm only without human-in-the loop performance)

Again, this is not an AI/ML algorithm in the diagnostic sense, but a powered mechanical device. Therefore, a "standalone algorithm only" performance is not relevant.

However, the "performance" of the device itself (independent of human diagnostic input, but certainly dependent on human operation and supervision) is extensively reported through:

• Non-Clinical Performance Data: Maximum Torque Testing, Cleaning Chemical Compatibility Testing, Component Life Cycle Testing, Durability Testing, Battery Life Cycle Testing, Storage and Transport Testing, Software verification and validation testing, Electrical safety testing, Electromagnetic compatibility testing – all reported as "PASS."
• Clinical Performance Data: The various functional mobility tests (10 MWT, 6 MWT, TUG, WISCI, FIM). These tests assess the patient's ability to ambulate with the device, which is essentially the device's functional performance in combination with the user. The device acts in conjunction with the user's postural changes and the supervision of a trained human.

7. The Type of Ground Truth Used

As discussed in #3, for this type of medical device, "ground truth" is established through:

• Objective Clinical Measurements: Quantifiable outcomes from standardized mobility tests (e.g., 10 Meter Walk Test, 6 Minute Walk Test, Timed Up and Go Test).
• Functional Independence Measures (FIM) and Walking Index for Spinal Cord Injury (WISCI) Scores: These are standardized clinical rating scales, where scores are determined by trained clinicians (Indego Specialists) based on observation of the patient's performance and the level of assistance required.
• Adverse Event Reporting: Direct observation and documentation of any adverse events during use.
• Patient and Trainer Feedback: Qualitative feedback on training adequacy and real-world use.

Unlike diagnostic tools, there isn't a "true positive/negative" outcome like disease presence confirmed by biopsy. Instead, the "ground truth" is the demonstrated functional ability and safety of the patient using the device as measured by validated clinical instruments.

8. The Sample Size for the Training Set

The text refers to "training" in two contexts:

1. Device training for users: Subjects undergo extensive training to learn how to use the Indego. This is training for the human user, not training data for an AI algorithm.
2. Training data for the device itself: If the device contained adaptable AI/ML components that learn from data, this section would be relevant. However, the description of the Indego's "on-board microprocessors receive signals from integrated sensors which provide information on the user's posture and tilt" and "user similarly controls of the Indego by means of postural changes" suggests deterministic or rule-based control rather than a deep learning model that would require a large "training set" of performance data. There is no mention of a machine learning "training set" size for the device's internal algorithms.

9. How the Ground Truth for the Training Set Was Established

As there's no explicitly described "training set" for an AI/ML algorithm within the device. Thus, the method for establishing "ground truth for the training set" is not applicable in the context of an AI/ML model for this device. The device's control mechanisms appear to be based on pre-programmed logic derived from engineering principles and biomechanics, rather than learned from a large dataset.

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The Indego® orthotically fits to the lower limbs and the trunk; the device is intended to enable individuals with spinal cord injury at levels T7 to L5 to perform ambulatory functions with supervision of a specially trained companion in accordance with the user assessment and training certification program. The device is also intended to enable individuals with spinal cord injury at levels T4 to T6 to perform ambulatory functions in rehabilitation institutions in accordance with the user assessment and training certification program. The Indego is not intended for sports or stair climbing.

Parker Hannifin's Indego® device is a wearable powered exoskeleton that actively assists individuals to stand and walk. Unique in design, the Indego consists of five (5) snap-together components (the lumbar/hip section, right and left upper leg sections, and right and left lower leg sections) weighing 26 pounds total. The hip component houses a rechargeable battery pack, central processor, and Bluetooth module, while each upper leg component houses two motors as well as embedded sensors and controllers.

On-board microprocessors receive signals from integrated sensors which provide information on the user's posture and tilt. This allows the device to function in a manner similar to the Segway personal mobility device, which is controlled by the user's tilt. A user similarly controls the Indego by means of postural changes (e.g., to walk forward, the user just leans forward). The technology of the design links the low weight and low profile to battery technology (smaller size), motors (smaller and more powerful), and micro controllers. Visual cues from LED lights on the hip unit and vibratory feedback inform both the therapist and patient of the status and mode of operation.

The Indego controls are self-contained, with crutches or a walker used solely for stability. Users can perform sit-to-stand and stand-to-sit transitions and walk along even or uneven terrain up to about five degree (5°) grades. Taller torso "wings" are provided to support users who may need additional trunk support while walking. A physical therapist can configure, operate, and monitor the device during therapy and training to make adjustments as needed. This is achieved through the support of a wireless application that will run on mobile/wifi connected smart devices such as an iPod or iPhone. Through the use of a Bluetooth connection, the Indego device's mode of operational parameters such as gait speed and step length/height, will be able to be changed or modified in real time. The device can be utilized in multiple indoor and outdoor locations within a rehabilitation setting or personal setting.

The provided text describes the regulatory submission for the Indego exoskeleton device. It details the device, its intended use, and a comparison to a predicate device (ReWalk). The filing includes non-clinical and clinical performance data to demonstrate safety and effectiveness.

Here's the breakdown of the acceptance criteria and study information:

Acceptance Criteria and Device Performance

Study Details:

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

   • Sample Size: 40 subjects.
   • Data Provenance: The document does not explicitly state the country of origin but implies a prospective clinical study ("The study was performed in compliance with Good Clinical Practices (GCP) with subjects enrolled in an IRB approved study that were consented for participation according to the intended use of the device..."). This suggests a controlled clinical trial setting.

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

   • The document does not mention the use of experts to establish a "ground truth" for the test set in the traditional sense of medical image analysis or diagnostic studies. Instead, the clinical study involved subjects using the device and their performance (walking speed, TUG test, level of assistance, perceived exertion) being measured directly. The "truth" here is the objective measurement of their functional abilities while using the device.

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

   • Not applicable in the context of this functional performance study. The data collected (e.g., walking speed, FIM scores, TUG test results) are objective measurements or standardized assessment scores, not subjective interpretations 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, a multi-reader multi-case (MRMC) comparative effectiveness study was not performed. This type of study typically applies to diagnostic or screening devices where human readers interpret medical images or data. The Indego is a powered exoskeleton for ambulation; its effectiveness is measured directly through functional performance metrics of the user.

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

   • The device, by its nature, inherently involves a human-in-the-loop. It is a wearable exoskeleton designed to assist individuals with spinal cord injury in performing ambulatory functions. Therefore, a standalone (algorithm only) performance assessment, independent of human interaction, is not relevant or applicable for this device. The software verification and validation were performed as part of non-clinical testing, but this is distinct from measuring "standalone performance" of a diagnostic algorithm.

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

   • The "ground truth" in this context is based on objective functional performance data using standardized clinical assessment tools (e.g., Ten Meter Walk Test, Timed Up-and-Go Test, WISC-II, FIM scores, Borg Rating of Perceived Exertion) and direct observation of subjects' abilities while using the device in a controlled clinical study environment.

7. The sample size for the training set:

   • The document does not explicitly mention a "training set" in the machine learning sense for the device's algorithms. The device's internal microprocessors receive signals from integrated sensors and function based on the user's posture and tilt (similar to a Segway). The development of these control algorithms would have involved engineering design, testing, and potentially iterative refinement, but the document does not specify a distinct "training set" of data in the manner of AI/ML models.

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

   • Given that a "training set" (as understood in machine learning) is not explicitly described, the method for establishing its "ground truth" is not detailed. The device likely relies on engineering principles and biomechanical models for its control algorithms, validated through non-clinical and clinical testing, rather than an AI model trained on a large dataset with established ground truth labels common in areas like image recognition. The "ground truth" for its functional performance is established through the clinical study mentioned above.

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