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HAL for Medical Use (Lower Limb Type) orthotically fits to the lower limbs and trunk; the device is intended for individuals with spinal cord injury at levels C4 to L5 (ASIA C, ASIA D) and T11 to L5 (ASIA A with Zones of Partial Preservation, ASIA B), who exhibit sufficient residual motor and movement-related functions of the hip and knee to trigger and control HAL.

HAL is a gait training device intended to temporarily help improve ambulation upon completion of the HAL gait training intervention. HAL must be used with a Body Weight Support system. HAL is not intended for sports or stair climbing. HAL gait training is intended to be used in conjunction with regular physiotherapy.

In preparation for HAL gait training, the controller can be used while the exoskeleton is not donned to provide biofeedback training through the visualization of surface electromyography bioelectrical signals recorded.

HAL is intended to be used inside medical facilities while under trained medical supervision in accordance with the user assessment and training certification program

HAL for Medical Use (Lower Limb Type) is a battery powered bi-lateral lower extremity exoskeleton that provides assistive torque at the knee and hip joints for gait training. HAL is comprised of a controller, a main unit, and sensor shoes. The device comes in 8 size variations (4 different leg lengths and 2 different hip widths) and weighs ~14 kg (30 lbs). The device uses legally marketed cutaneous electrodes (up to 18 electrodes) to record surface electromyography bioelectrical signals of the hip and knee extensor and flexor muscles when the device is used in Cybernic Voluntary Control (CVC) mode. This mode provides assistive torque at the corresponding joint (e.g., hip or knee) using sufface electromyography bioelectrical signals that are processed using a propriety signal processing algorithm. The propriety processing algorithm allows the device to detect surface electromyography bioelectrical signals to control the HAL device in CVC mode and provide visualization of the surface electromyography bioelectrical signals during biofeedback training. The assistive torque can be adjusted using three parameters: sensitivity level. torque turner. and balance turner. The device can also provide two additional modes: Cybernic Autonomous Control (CAC) mode and Cybernic Impedance Control (CIC) mode. CAC mode provides assistive torque leq trajectories based on postural cues and sensor shoe measurements. CIC mode provides torque to compensate for frictional resistance of the motor based on joint motion. CIC mode does not provide torque assistance for dictating joint trajectories. A trained medical professional (i.e., physician, physical therapist, etc.) can configure, operate, and monitor the device during gait training to make adjustments as needed.

Patients must exhibit sufficient residual motor and movement-related functions of the hip and knee to trigger and control HAL. The patient must be supported by a Body Weight Support (BWS) system before donning the device and during device use. The BWS must not be detached from the patient before doffing this device. HAL is not intended to provide sit-stand or stand-sit movements. HAL is capable of gait speeds up to approximately 2 km/hour on level ground. HAL is not intended for sports or stairclimbing.

In preparation to using HAL, the controller can be used while the exoskeleton is not donned to provide biofeedback training through the visualization of surface electromyography bioelectrical signals recorded.

HAL is intended to be used in conjunction with regular physiotherapy. HAL is intended to be used inside a medical facility under the supervision of trained medical professionals who have successfully completed the HAL training program.

Here's a breakdown of the acceptance criteria and study information for the HAL for Medical Use (Lower Limb Type), based on the provided document:

Acceptance Criteria and Device Performance

The document doesn't explicitly state "acceptance criteria" in a separate, quantifiable table for clinical performance endpoints. Instead, it presents the results of two clinical studies and highlights whether the observed improvements are statistically and clinically significant. The key clinical measures used to demonstrate effectiveness are:

Note: The "acceptance criteria" in the table above are inferred from the document's emphasis on demonstrating "statistically significant improvement" and improvement values exceeding "clinically significant" thresholds (MCID) for the 10MWT and 6MWT. For WISCI II, "mean gain of 1.69 levels" with a p-value of <0.001 suggests an accepted improvement. For adverse events, the lack of serious events and resolution of mild events indicates accepted safety.

The document also details numerous non-clinical performance criteria which are met through bench testing to ensure safety and functionality:

• Stopper Strength Test: Conformance maintained after 100 cycles, expected to endure impact.
• Consecutive Landing Test: All 3 samples withstood 3,000,000 cycles without failure, demonstrating sufficient durability.
• Effective Output Test (Torque & Angular Velocity): Output found to meet specifications and be within human tolerance for angular velocity.
• Driving Parts Performance Test: Actual torque output compared to intended torque falls within criteria range.
• Joint angle measurement: Accuracy verified to meet specifications.
• Body trunk absolute angle measurement: Sufficiently detects stable posture for safety and effectiveness.
• Plantar load measurement: Sufficiently detects planting and lifting to determine leg phase for safety and effectiveness.
• Surface Electromyography Bioelectrical signal measurement performance: Accuracy for all measurements (input impedance, common-mode rejection ratio, frequency characteristics) verified to meet specifications.
• Ankle Durability Test: All 3 samples withstood 300,000 impacts (5 years' worth) without failure, demonstrating sufficient durability.

Study Details

2. Sample Size and Data Provenance

DE-01 Clinical Study (Pilot Study):

• Test Set Sample Size: 8 subjects
• Data Provenance: Prospective, conducted at BG University Hospital Bergmannsheil (Germany, inferred from "Bergmannsheil").

DE-02 Clinical Study:

• Test Set Sample Size: 55 subjects
• Data Provenance: Prospective, conducted at BG University Hospital Bergmannsheil (Germany, inferred from "Bergmannsheil").

3. Number of Experts and Qualifications for Ground Truth

The clinical studies involved human assessment of functional outcomes (10MWT, 6MWT, WISCI II). While these are quantitative measures, the execution of the tests and interpretation would be by trained medical professionals. The document states: "The training was supervised by a physiotherapist and a medical doctor." This indicates at least two types of qualified experts were involved in the clinical assessment and potentially in establishing the "ground truth" (i.e., the measured functional scores). Specific years of experience are not provided.

4. Adjudication Method

The document does not explicitly describe an adjudication method for the clinical outcomes. Since the endpoints (10MWT speed, 6MWT distance, WISCI II score) are objective measurements, it is likely that standard clinical protocols were followed for their assessment, which inherently involves some level of consensus or single objective measurement by the supervising medical staff. Formal multi-expert adjudication for "ground truth" as might be seen in image classification is not applicable here.

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

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not explicitly done. The studies were single-arm, uncontrolled interventional studies designed to show improvement within the patient group (before vs. after intervention with HAL) rather than comparing performance against other devices or human readers. The clinical studies focus on the patient's functional improvement without the HAL device after a training intervention, suggesting an "algorithm only without human-in-the-loop performance" in terms of the test subjects' measurement, but the intervention itself is human-in-the-loop (supervised by medical professionals).

6. Standalone (Algorithm Only) Performance

The clinical effectiveness studies (DE-01 and DE-02) do assess a form of standalone performance in the sense that the primary endpoints (10MWT, 6MWT, WISCI II) are measured without wearing the HAL device after the training intervention. This means they are measuring the residual functional improvement in the patient's own ambulation capability after HAL-assisted gait training, rather than the performance of the HAL device itself during use.

The non-clinical bench testing, however, is a form of standalone performance evaluation for the device's mechanical and electrical components and its internal measurement systems (e.g., joint angle sensing, EMG signal measurement accuracy).

7. Type of Ground Truth Used

The ground truth for the clinical studies is functional outcome measures as assessed by standard clinical tests:

• 10 Meter Walk Test (speed)
• 6 Minute Walk Test (distance)
• Walking Index for Spinal Cord Injury II (WISCI II) score

These are objective, quantifiable measures of ambulation capability.

8. Sample Size for the Training Set

The document does not specify a separate "training set" in the context of machine learning model development. The HAL device (Lower Limb Type) is a powered exoskeleton that uses bioelectrical signals and postural cues. While it has a "propriety signal processing algorithm," the document doesn't detail if this algorithm was "trained" on a specific dataset of patients or how large that dataset was. The clinical studies (N=8 and N=55) represent validation/testing of the device's overall effectiveness in improving patient ambulation and its safety.

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

Given that a specific "training set" for an AI/algorithm is not detailed, the ground truth establishment method for such a set isn't provided. The "propriety signal processing algorithm" is mentioned as processing surface electromyography bioelectrical signals to control the device and provide visualization for biofeedback. How this algorithm was developed or optimized (i.e., its "training" process and associated "ground truth") is not disclosed in this regulatory summary.

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