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For use only in healthy subjects for Measurement of:

Estimated: Skeletal Muscle Mass, Extra-Cellular Water (ICW), Total Body Water (ICW), Total Body Water (TBW), ECW/TBW, Body Fat, Percentage of Body Fat (PBF), Body Lean + Dry Lean, Metabolic Rates), Segmental Lean Mass, Segmental Fat Mass, % Segmental Body Fat, Energy Expenditure of Activity, Visceral Fat Area (VFA), Visceral Fat Level, Segmental Body Water, Percent Body Shape Graph, Weight Control, Fat Control, Muscle Control, Segmental ECW/TBW, Segmental ICW, TBW/LBM, Leg Lean Mass, Fitness Score, AC (Arm Circumference)

Actual: Weight, Body Mass Index (BMI) and Impedance Values, Height [which can require the entry of Height], Resistance Values [only for InBody S10], Reactance Values [only for InBody770, InBody S10], Phase Angle [only for InBody770, InBody S10]

Impedance plethysmographic devices are used to estimate peripheral blood flow by measuring electrical impedance changes in a region of the body such as the arms and legs. Multi-frequency and segmental bioelectrical impedance analysis can estimate the distribution of body water (total body water; intra-cellular water), and can correlate with fluid compartmentalization. Assuming that body lean mass is hydrated in a constant and uniform manner; bioelectrical impedance analysis can be used to estimate body lean mass and fat mass.
These devices are impedance plethysmograph body composition analyzers. These devices determine body composition parameters based on bioelectrical impedance analysis (BIA). BIA relies on the differing behavior of biological tissues in response to an applied electrical current. Lean tissue is generally highly conductive because it contains large amounts of bound water and electrolytes, while fat tissue and bone are relatively poor conductors. By analyzing the response to electrical signals, BIA thereby permits differentiation of lean tissue, fat, and water and, in some instances, derivation of related body composition parameters. The total impedance resulting from BIA incorporates both resistance and capacitance components. Impedance plethysmographic devices are used to estimate peripheral blood flow by measuring electrical impedance changes in a region of the body such as the arms and legs. Multi-frequency and segmental bioelectrical impedance analysis can estimate the distribution of body water (total body water; intra-cellular water; extra-cellular water), and can correlate with fluid compartmentalization. Assuming that body lean mass is hydrated in a constant and uniform manner; bioelectrical impedance analysis can be used to estimate body lean mass and fat mass. Body composition analysis results may be of value to health care professionals in their management of the relative balance and levels of fat and lean tissue

The Biospace Body Composition Analyzers (Models InBody770, InBody570, InBody S10, InBody230) were evaluated through a clinical study to demonstrate substantial equivalence to previously cleared predicate devices. The primary method of evaluation involved comparing the performance of the new devices against predicate devices across a range of body composition metrics.

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" with numerical thresholds for performance. Instead, it relies on demonstrating comparable performance to predicate devices already cleared by the FDA, with "very nearly 1.00" correlation coefficients between the new devices and predicates as the key performance indicator.

2. Sample Size and Data Provenance:

• Test Set Sample Size: Approximately 80 patients.
• Data Provenance: The document does not explicitly state the country of origin. Given Biospace Corporation Limited is based in Seoul, Korea, it is highly probable the data originated from Korea. The study appears to be prospective as it states "We conducted clinical testing on each model."

3. Number and Qualifications of Experts for Ground Truth:

The document does not mention using experts to establish ground truth for the test set in the traditional sense (e.g., radiologists interpreting images). The study focuses on comparing the output of the new devices against predicate devices, implying that the predicate devices themselves serve as a form of "reference" or "ground truth" for comparative effectiveness in this context.

4. Adjudication Method:

Given that the ground truth appears to be based on the output of predicate devices, an adjudication method in the form of expert consensus is not applicable or mentioned in the document.

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

An MRMC study was not conducted as this device does not involve human readers interpreting diagnostic images. The study compared device outputs directly. Therefore, there is no effect size of human improvement with or without AI assistance to report.

6. Standalone Performance Study:

A standalone performance study of the algorithm (if "algorithm" refers to the core BIA calculation logic) was implicitly done in the context of comparing the new devices against predicates. The reported "very nearly 1.00" correlation coefficients represent the standalone performance of the new devices relative to the established performance of the predicate devices. The study compares the device's measurement capabilities rather than an AI algorithm without human intervention.

7. Type of Ground Truth Used:

The primary "ground truth" for comparison was the measurements obtained from predicate devices. This is a form of comparative validation against established medical devices with a known performance profile.

8. Sample Size for the Training Set:

The document does not provide information regarding a separate training set or its sample size. As a medical device based on bioelectrical impedance analysis, its underlying principles and algorithms might be well-established, potentially requiring calibration and validation rather than extensive machine learning-style "training" on a specific dataset for output generation in the same way an AI image classification model would.

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

As no explicit training set is mentioned in the provided text, the method for establishing its ground truth is not discussed.

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The Biospace blood pressure monitor is designed to measure blood pressure (diastolic and systolic) and pulse rate in adult patients with arm circumference range between 17cm - 42cm. (BPBIO320n is the same device as the BPBIO320 and has same specifications except it has no printer module.)

BPBIO320/BPBIO320n is for use by medical professionals or at home and is a noninvasive blood pressure measurement system intended to measure the diastolic and systolic blood pressures and pulse rate of an adult individual by using a non-invasive technique in which an inflatable cuff is wrapped around the upper arm. The cuff size is 545 × 120 (mm) and the arm circumference range is between to 17cm - 42cm. BPBIO320/BPBIO320n is designed and manufactured according to ANSI/AAMI SP10 manual, electronic or automated sphygmanometers. BPBIO320/BPBIO320n can measure systolic, diastolic pressure and pulse rate on the principle of oscillometric on inflation. The oscillometric method detects volume displacements within the artery and senses pressure variations within the blood pressure cuff during inflation.

Here's a breakdown of the acceptance criteria and study information for the BPBIO320 and BPBIO320n blood pressure monitors, based on the provided 510(k) summary:

Acceptance Criteria and Reported Device Performance

Note: The document explicitly states that the device met "all applicable requirements of the standard" for ANSI/AAMI SP10. The table above focuses on the specific numerical performance metrics that are directly comparable to the predicate or listed as a specification for the proposed device.

Study Information

The document describes a clinical test conducted to demonstrate compliance with ANSI/AAMI SP10, especially given the difference in measurement methodology (inflation vs. deflation) compared to the predicate device.

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

• Sample Size: Not explicitly stated in the provided text. The document only mentions "a new clinical test is done in accordance with ANSI/AAMI SP10." The ANSI/AAMI SP10 standard itself specifies minimum subject requirements for clinical validation (e.g., typically a minimum of 85 subjects with specific blood pressure ranges).
• Data Provenance: Not explicitly stated (e.g., country of origin, retrospective/prospective). It simply refers to "a new clinical test."

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

• Not explicitly stated. For blood pressure monitor validation, ground truth is typically established by trained human observers using a mercury sphygmomanometer or an equivalent reference device, not necessarily by "experts" in the sense of radiologists. The ANSI/AAMI SP10 standard details the requirements for these observers (e.g., blinded measurements, simultaneous readings, specific training).

4. Adjudication method for the test set:

• Not explicitly stated. The ANSI/AAMI SP10 standard outlines specific protocols for comparing the automated device's readings to reference measurements, which often involves multiple observers and statistical analysis, but the exact adjudication method (e.g., 2+1, 3+1) is not detailed in this summary.

5. If a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was done:

• No. This type of study (MRMC) is typically associated with imaging devices where multiple readers interpret cases. For a blood pressure monitor, the "effectiveness" is assessed by its accuracy against a reference measurement, not by human readers interpreting the device's output.

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

• Yes, implicitly. The clinical test described is a standalone performance evaluation of the device as it measures blood pressure and pulse rate directly. There isn't a human interpreting an "algorithm output" in the traditional sense; the device itself provides the final measurement.

7. The type of ground truth used:

• The ground truth would be reference blood pressure measurements obtained simultaneously by trained observers using a validated method (e.g., mercury sphygmomanometer) as mandated by the ANSI/AAMI SP10 standard.

8. The sample size for the training set:

• Not applicable/Not stated. Blood pressure monitors like the BPBIO320/BPBIO320n are hardware devices that use an oscillometric method. While there's an "arithmetic" (algorithm) involved, especially given the inflation detection method, the device is not typically "trained" on a dataset in the way a machine learning algorithm would be. The design and parameters of the oscillometric algorithm are established during development and then validated through clinical testing.

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

• Not applicable. See point 8. The "ground truth" for the development of the oscillometric algorithm would come from physiological principles and previous research relating cuff pressure oscillations to arterial blood pressure, rather than a specific "training set" with established ground truth in the context of supervised machine learning.

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For use only in healthy subjects for Measurement of: Estimated : Skeletal muscle mass, Extra-Cellular Water (ECW), Intra-Cellular Water (ICW), Total Body Water, (TBW), Body Fat, Body Lean + Dry Lean, Metabolic Rates, Segmental Lean Mass. Actual : Weight, Body Mass Index (BMI),and Impedance Values

Model Inbody 230 is an impedance plethysmograph body composition analyzer. This device determines body composition parameters based on bioelectrical impedance analysis (BIA). BIA relies on the differing behavior of biological tissues in response to an applied electrical current. Lean tissue is generally highly conductive because it contains large amounts of bound water and electrolytes, while fat tissue and bone are relatively poor conductors. By analyzing the response to electrical signals, BIA thereby permits differentiation of lean tissue, fat, and water and, in some instances, derivation of related body composition parameters. The total impedance resulting from BIA incorporates both resistance and capacitance components.

The provided text describes the Biospace Body Composition Analyzer, Model InBody 230, and its substantial equivalence to predicate devices, but it does not contain a detailed study report with specific acceptance criteria and performance data in a format that lends itself to a direct table of acceptance criteria vs. device performance, nor does it explicitly detail the methodology of a study to prove it meets acceptance criteria.

However, based on the information provided, particularly the "Substantial Equivalence Chart" and the "Conclusion" section, we can infer the acceptance criteria are implicitly met by demonstrating substantial equivalence to the existing predicate devices. The document states that "After analyzing both bench and clinical testing data, it is the conclusion of Biospace that the Model [InBody 230] is as safe and effective as the predicate devices... and has been validated via human clinical trial."

Given the limitations of the provided text, I will construct a response that extracts the relevant information and indicates where detailed information is not present.

1. Table of Acceptance Criteria and Reported Device Performance

The document does not explicitly state numerical acceptance criteria (e.g., specific accuracy thresholds for body fat percentage). Instead, substantial equivalence is claimed based on comparable intended use, technology, and performance to predicate devices. The "reported device performance" is implied to be "as safe and effective as the predicate devices" and "validated via human clinical trial."

Note: The primary "acceptance criterion" demonstrated here is "substantial equivalence" to the listed predicate devices, rather than meeting specific quantitative performance targets like sensitivity, specificity, or accuracy percentages. The document does not provide a study breakdown with numerical results against pre-defined thresholds.

2. Sample Size and Data Provenance for Test Set

The document mentions "human clinical trial" and "clinical testing data" but does not specify the sample size used for the test set. It also does not specify the data provenance (e.g., country of origin, retrospective or prospective nature) for any clinical data used.

3. Number of Experts and Qualifications for Ground Truth

The document does not provide information on the number of experts used to establish ground truth or their qualifications. The study methodology is not detailed in the provided text.

4. Adjudication Method for Test Set

The document does not specify any adjudication method (e.g., 2+1, 3+1, none) for a test set.

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

There is no mention of a Multi-Reader Multi-Case (MRMC) comparative effectiveness study or any effect size for human readers improving with or without AI assistance. This device is a measurement tool, not an AI-assisted diagnostic imaging interpretation system.

6. Standalone Performance Study

The document states that the device was "validated via human clinical trial" and that "bench and clinical testing data" support its safety and effectiveness. This implies a standalone performance evaluation of the device's measurements. However, specific details of this standalone performance, such as metrics (e.g., accuracy, precision) or comparative data against a gold standard, are not provided. The claim is primarily about substantial equivalence to predicate devices, which also perform standalone measurements.

7. Type of Ground Truth Used

The document does not explicitly state the type of "ground truth" used in the human clinical trial. For body composition analyzers, gold standards usually involve methods like DEXA (Dual-energy X-ray Absorptiometry), hydrostatic weighing, or isotopic dilution, but this is not specified here. The absence of specific ground truth details suggests that the equivalence might primarily rely on comparison of outputs and operational characteristics with existing BIA devices deemed safe and effective.

8. Sample Size for Training Set

The document does not provide information on a separate "training set" or its sample size. This type of device (Bioelectrical Impedance Analysis) typically relies on established biophysical models rather than a machine learning training paradigm that would have a distinct training set in the AI sense.

9. How Ground Truth for Training Set Was Established

Since a distinct "training set" in the machine learning sense is not indicated, the document does not describe how ground truth for any such set was established. The device's operation is based on bioelectrical impedance principles, which leverage physiological constants and empirical equations derived from research, rather than a data-driven training process in the way an AI model would be trained.

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For use only in healthy subjects for Measurement Of: Estimated : Extra-Cellular Water (ECW), Intra-Cellular Water (ICW),Total Body Water, (TBW), ECW to TBW ratio, Body Fat, Body Lean + Dry Lean, Metabolic Rates, Segmental Lean Mass Actual : Weight, (except for model S20, which requires the manual entry of weight) Body Mass Index (BMI),and Impedance Values

Models Inbody 520, Inbody 720, and Inbody S20 are body composition analyzers. The devices determine body composition parameters based on bioelectrical impedance analysis (BIA). BIA relies on the differing behavior of biological tissues in response to an applied electrical current. Lean tissue is generally highly conductive because it contains large amounts of bound water and electrolytes, while fat tissue and bone are relatively poor conductors. By analyzing the response to electrical signals, BIA thereby permits differentiation of lean tissue, fat, and water and, in some instances, derivation of related body composition parameters. The total impedance resulting from BIA incorporates both resistance and capacitance components.

The provided K052646 document for Biospace Corporation Limited's InBody Body Composition Analyzers (Models 520, 720, and S20) does not contain detailed acceptance criteria, specific study designs, or reported device performance metrics as requested. Instead, it focuses on demonstrating substantial equivalence to a predicate device (Biospace Body Composition Analyzer Model InBody 3.0, K042528) to obtain 510(k) clearance from the FDA.

The document indicates that "bench and clinical testing indicates that the new device is as safe and effective as the predicate devices," but it does not provide the quantitative results or specific acceptance criteria for these tests. The comparison table primarily highlights the features and indications for use, including the different frequencies used for impedance measurements, between the new devices and the predicate.

Therefore, many of the requested details cannot be extracted directly from this document. Below is an attempt to address the points based on the available information and what can be inferred about a 510(k) submission for substantial equivalence.

Acceptance Criteria and Study for Biospace Body Composition Analyzers (Models InBody 520, InBody 720, and InBody S20)

The provided submission primarily focuses on demonstrating "substantial equivalence" to a predicate device, as opposed to establishing specific performance acceptance criteria and proving them through detailed studies with quantitative results. The core of a 510(k) is to show that a new device is as safe and effective as a legally marketed predicate device, not necessarily that it meets pre-defined acceptance criteria for novel performance claims.

1. Table of Acceptance Criteria and Reported Device Performance

Based on the document, explicit quantitative acceptance criteria and reported device performance metrics (e.g., accuracy, precision, correlation coefficients against a gold standard) are not detailed. The document generally states: "The results of bench and clinical testing indicates that the new device is as safe and effective as the predicate devices."

The comparison table (Section 6) focuses on functional equivalence, listing the Indications for Use and Analysis Method as identical to the predicate device, but expands the Operating parameters (Frequency) for the new models (InBody 720 and S20) compared to the predicate and InBody 520. This suggests that the "acceptance criteria" were likely related to demonstrating similar measurements and safety profiles to the predicate, rather than meeting specific numerical performance targets against a true gold standard.

Missing Information: The document does not provide actual numerical data for accuracy, precision, bias, correlation coefficients, or any other specific performance metrics from the bench or clinical testing mentioned.

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

This information is not provided in the document. For a 510(k) submission based on substantial equivalence, clinical data might involve healthy volunteers to demonstrate comparable measurements to the predicate device, but specific sample sizes and data provenance (e.g., country of origin, retrospective/prospective nature) are not disclosed in this summary.

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

This information is not provided. Body composition analysis, especially with BIA, usually relies on reference methods (e.g., DEXA, hydrodensitometry) or other validated BIA devices rather than expert consensus on images. The "ground truth" for the test set would likely be measurements from the predicate device or a clinical gold standard, if such a study was performed.

4. Adjudication Method (e.g., 2+1, 3+1, none) for the Test Set

This information is not provided. As the device measures quantitative physiological parameters rather than interpreting images or clinical signs, an adjudication method for "test set" interpretation is generally not applicable in the same way it would be for diagnostic imaging.

5. If a Multi Reader Multi Case (MRMC) Comparative Effectiveness Study was done

This information is not provided. MRMC studies are typically used in diagnostic imaging to assess human reader performance with and without AI assistance. This device is a quantitative measurement tool (body composition analyzer), not an imaging interpretation aid, so an MRMC study is highly unlikely to have been performed or relevant for this type of submission.

6. If a Standalone (i.e. algorithm only without human-in-the-loop performance) was done

The device itself is a standalone algorithm/device for body composition analysis. The "performance" described would inherently be the algorithm's performance in providing measurements. The document generally states "bench and clinical testing," which implies direct performance evaluation of the device in a standalone capacity. No human-in-the-loop component is mentioned or suggested for the primary function of body composition measurement.

7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

The specific type of "ground truth" used for any clinical testing (if conducted beyond direct comparison to the predicate) is not explicitly stated. However, for body composition analyzers like the InBody series, the ground truth typically involves:

• Validated Reference Methods: Such as Dual-energy X-ray Absorptiometry (DEXA), hydrodensitometry (underwater weighing), or isotope dilution for water compartments.
• Comparison to a Predicate Device: In a 510(k) context, a common approach is to demonstrate agreement with the legally marketed predicate device (Biospace Body Composition Analyzer Model InBody 3.0, K042528) through correlation studies or Bland-Altman analysis.

Given the 510(k) pathway, it is most probable that comparability to the predicate device was the primary "ground truth" for demonstrating substantial equivalence.

8. The Sample Size for the Training Set

This information is not provided. BIA devices typically use mathematical models and equations to convert impedance values into body composition parameters. While these models might be "trained" or derived from large population datasets, the details of such training sets (size, characteristics, data provenance) are not part of this 510(k) summary. This submission focuses on the performance of the device (applying its algorithms) rather than the development of the algorithms themselves.

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

This information is not provided. If mathematical models within the device's software were derived from population data, the ground truth for establishing those models would typically come from a combination of gold-standard body composition methods (e.g., DEXA, hydrodensitometry) applied to a diverse cohort. However, this level of detail is beyond the scope of this 510(k) submission, which assumes the underlying BIA principles and algorithms are already established or sufficiently similar to a predicate.

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