(172 days)
Medical HAL Lower Limb Type orthotically fits to the lower limbs and trunk; 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.
The device is intended for individuals with:
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spinal cord iniurv at levels C4 to L5 (ASIA C. ASIA D) and T11 to L5 (ASIA A with Zones of Partial Preservation, ASIA B);
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post stroke paresis
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paraplegia due to progressive neuromuscular diseases (spinal muscular atrophy, spinal and bulbar muscular atrophy, amyotrophic lateral sclerosis, Charcot-Marie-Tooth disease, distal muscular dystrophy, inclusion body myositis, congenital myopathy, muscular dystrophy)
-cerebral palsy and are 12 years or older
-spastic paraplegia caused by either HTLV-1 Associated Myelopathy (HAM) or hereditary spastic paraplegia (HSP)
who exhibit sufficient residual motor and movement-related functions of the hip and knee to trigger and control HAL.
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 healthcare facilities while under trained medical supervision in accordance with the user assessment and training certification program.
Medical HAL Lower Limb Type is a battery powered bi-lateral ower 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 in 30 size variations (variation same as predicate: 3 different leg lengths, 2 different leg lengths, 2 different waist widths >> total 24. New size variation: 3 different leg configurations, 1 leg lengths, 2 different waist widths >> total 6) and weighs ~9.5 kg (21 lbs). The main difference between the Model ML05 and ML07 is the leglengths. ML05 has S.M, L, XL sizes, while ML07 has 2S sizes. The device uses legally marketed electrodes (up to 18 electrodes) to record surface electromyography bioelectrical signals that are processed using a propriety signal processing algorithm. The propriety processing algorithm allows the 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 tuner, and balance tuner. The device can also provide two additional modes: Cybernic Autonomous Control (CAC) mode and Cybernic Impedance Control (ClC) mode. CAC mode provides assistive torque leg trajectories based on postural cues and sensor shoe measurements. CC 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., 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 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.
The provided text, a 510(k) summary for the Medical HAL Lower Limb Type (HAL-ML), describes the device, its intended use, and its equivalence to a predicate device (HAL for Medical Use (Lower Limb Type), K201559). It primarily focuses on regulatory approval and equivalence, particularly regarding the expansion of indications for use to include Cerebral Palsy and Spastic Paraplegia.
While the document references "clinical data to support the safety and efficacy" and "clinical evaluation procedure," it does not provide a detailed breakdown of acceptance criteria or the specific study results proving the device meets those criteria in the format requested. It states that the "nonclinical and clinical tests submitted demonstrate that the device is as safe and as effective, and performs as well as the legally marketed device cleared as K201559." However, it does not offer the granular information needed to fulfill all aspects of your request (e.g., specific performance metrics, sample sizes for test sets, expert qualifications, or MRMC study details).
Therefore, based only on the provided text, I can infer some information regarding the clinical evaluation but cannot fully populate the table or answer all sub-questions as the detailed study design, acceptance criteria with numerical performance data, and other specifics are not disclosed in this regulatory summary.
Here's an attempt to answer your questions based on the available information, with clear indications where the information is not provided in the text:
1. A table of acceptance criteria and the reported device performance
The document does not specify quantitative acceptance criteria or report specific performance metrics for the efficacy of the device in a table format. It broadly states that the clinical evaluation "results are sufficient to support the claims identified in the Indications for Use for this submission" and that the device is "sufficiently safe".
2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
- Sample Size for Test Set: Not provided. The document mentions clinical evaluations for five indication groups but does not state the number of subjects in these evaluations.
- Data Provenance: Not provided. The country of origin of the data (e.g., Japan, where the manufacturer is located) and whether the studies were retrospective or prospective are not mentioned.
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience)
This information is not provided in the document. Ground truth for a device like HAL-ML would likely refer to clinical outcomes or functional improvements, which are assessed by medical professionals during the study, rather than "experts establishing ground truth" in the same way it might apply to an imaging AI algorithm. The document mentions "trained medical professionals (i.e., physical therapist, etc.)" configure, operate, and monitor the device, but not their specific role in establishing ground truth for a study.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
This information is not provided.
5. 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
An MRMC study is typically performed for diagnostic imaging devices where human readers interpret medical images. This type of study is not applicable to the Medical HAL Lower Limb Type, which is a gait training device. Therefore, no information on MRMC studies or human reader improvement with AI assistance is present or relevant here.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
The device is a physical exoskeleton used for gait training, highly dependent on human interaction (patient and trained medical professional). It's not an algorithm-only device. The "propriety processing algorithm" processes sEMG signals to control the device, but its performance is intrinsically tied to the Human-in-the-loop interaction for gait training. Therefore, a "standalone algorithm only" performance study in the typical AI sense is not relevant or described.
7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)
The document states "The safety and effectiveness of the subject device is demonstrated through the following clinical evaluation procedure for each of the 5 indication groups... The evaluation results are sufficient to support the claims identified in the Indications for Use." This strongly implies that the ground truth would be based on clinical outcomes data related to ambulation improvement, safety, and effectiveness in the specified patient populations. However, the specific metrics or "ground truth" definitions (e.g., specific scores on mobility scales) are not detailed.
8. The sample size for the training set
The document describes clinical evaluation for the safety and effectiveness of the device as a whole. It does not mention a "training set" in the context of an AI/ML model for which a distinct training set would be used. The "propriety processing algorithm" is part of the device's functionality, but the document does not provide details about its development, including specific training set sizes if machine learning were used this way.
9. How the ground truth for the training set was established
As there is no mention of a "training set" in the context of an AI/ML model with externally established ground truth for training purposes, this information is not provided. The algorithm processes sEMG signals to control the device, which is an engineering function, not necessarily a machine learning model that requires a distinct "training set ground truth" in the way a diagnostic AI would.
In summary, the provided 510(k) summary serves as a regulatory document for substantial equivalence, not a detailed scientific publication of clinical trial results. It confirms that clinical evaluations were performed to support the expanded indications but does not provide the granular data, methodology, or specific acceptance criteria and performance statistics that you've requested beyond a general statement of safety and effectiveness.
§ 890.3480 Powered lower extremity exoskeleton.
(a)
Identification. A powered lower extremity exoskeleton is a prescription device that is composed of an external, powered, motorized orthosis that is placed over a person's paralyzed or weakened limbs for medical purposes.(b)
Classification. Class II (special controls). The special controls for this device are:(1) Elements of the device materials that may contact the patient must be demonstrated to be biocompatible.
(2) Appropriate analysis/testing must validate electromagnetic compatibility/interference (EMC/EMI), electrical safety, thermal safety, mechanical safety, battery performance and safety, and wireless performance, if applicable.
(3) Appropriate software verification, validation, and hazard analysis must be performed.
(4) Design characteristics must ensure geometry and materials composition are consistent with intended use.
(5) Non-clinical performance testing must demonstrate that the device performs as intended under anticipated conditions of use. Performance testing must include:
(i) Mechanical bench testing (including durability testing) to demonstrate that the device will withstand forces, conditions, and environments encountered during use;
(ii) Simulated use testing (
i.e., cyclic loading testing) to demonstrate performance of device commands and safeguard under worst case conditions and after durability testing;(iii) Verification and validation of manual override controls are necessary, if present;
(iv) The accuracy of device features and safeguards; and
(v) Device functionality in terms of flame retardant materials, liquid/particle ingress prevention, sensor and actuator performance, and motor performance.
(6) Clinical testing must demonstrate a reasonable assurance of safe and effective use and capture any adverse events observed during clinical use when used under the proposed conditions of use, which must include considerations for:
(i) Level of supervision necessary, and
(ii) Environment of use (
e.g., indoors and/or outdoors) including obstacles and terrain representative of the intended use environment.(7) A training program must be included with sufficient educational elements so that upon completion of training program, the clinician, user, and companion can:
(i) Identify the safe environments for device use,
(ii) Use all safety features of device, and
(iii) Operate the device in simulated or actual use environments representative of indicated environments and use.
(8) Labeling for the Physician and User must include the following:
(i) Appropriate instructions, warning, cautions, limitations, and information related to the necessary safeguards of the device, including warning against activities and environments that may put the user at greater risk.
(ii) Specific instructions and the clinical training needed for the safe use of the device, which includes:
(A) Instructions on assembling the device in all available configurations;
(B) Instructions on fitting the patient;
(C) Instructions and explanations of all available programs and how to program the device;
(D) Instructions and explanation of all controls, input, and outputs;
(E) Instructions on all available modes or states of the device;
(F) Instructions on all safety features of the device; and
(G) Instructions for properly maintaining the device.
(iii) Information on the patient population for which the device has been demonstrated to have a reasonable assurance of safety and effectiveness.
(iv) Pertinent non-clinical testing information (
e.g., EMC, battery longevity).(v) A detailed summary of the clinical testing including:
(A) Adverse events encountered under use conditions,
(B) Summary of study outcomes and endpoints, and
(C) Information pertinent to use of the device including the conditions under which the device was studied (
e.g., level of supervision or assistance, and environment of use (e.g., indoors and/or outdoors) including obstacles and terrain).