K150494 · Proteus Digital Health, Inc. · OZW · Jun 27, 2015 · General Hospital
Device Facts
Record ID
K150494
Device Name
Proteus Digital Health Feedback Device
Applicant
Proteus Digital Health, Inc.
Product Code
OZW · General Hospital
Decision Date
Jun 27, 2015
Decision
SESE
Submission Type
Traditional
Regulation
21 CFR 880.6305
Device Class
Class 2
Indications for Use
The Proteus® Digital Health Feedback Device consists of a miniaturized, wearable sensor for ambulatory recording of physiological and behavioral metrics such as heart rate, activity, body angle relative to gravity (body position), and time-stamped patient-logged events, including events signaled by the co-incidence with, or co-ingestion with, the ingestible sensor accessory. When the ingestible sensor is ingested, the Proteus Digital Health Feedback Device is intended to log, track and trend intake times. When co-ingested with medication, the tracking and trending of intake times may be used as an aid to measure medication adherence. The Proteus Digital Health Feedback Device may be used in any instance where quantifiable analysis of event-associated physiological and behavioral metrics is desirable, and enables unattended data collection for clinical and research applications.
Device Story
System comprises wearable sensor, ingestible sensor, and software application. Wearable sensor collects heart rate (biopotential), activity/body angle (accelerometer), skin temperature (thermistor), and patient-logged events. Ingestible sensor, embedded in inactive tablet, activates in stomach via bio-galvanic power; communicates unique identifier to wearable sensor via volume conduction. Wearable sensor transmits data to software application for processing, analysis, and display. Used in clinical/research settings for unattended data collection; aids healthcare providers in assessing medication adherence and circadian patterns. Benefits include objective tracking of medication intake and physiological trends.
Clinical Evidence
No clinical data were required; substantial equivalence supported by bench testing and design verification.
Technological Characteristics
Wearable sensor: Ovoid/rectangular form factor, LiMn coin cell battery, 4-16MB memory. Sensors: Biopotential amplifiers (heart rate, impedance), 3-axis accelerometer (activity, body angle), thermistor (skin temperature). Ingestible sensor: Bio-galvanically powered circuit using volume conduction. Software: Proprietary algorithms for R-wave detection and physiological metric quantification. Standards: ANSI/AAMI EC 13 for heart rate.
Indications for Use
Indicated for patients requiring ambulatory monitoring of physiological and behavioral metrics (heart rate, activity, body position) and medication adherence tracking via ingestible sensor technology.
Regulatory Classification
Identification
An ingestible event marker is a prescription device used to record time-stamped, patient-logged events. The ingestible component links wirelessly through intrabody communication to an external recorder which records the date and time of ingestion as well as the unique serial number of the ingestible device.
Special Controls
In combination with the general controls of the FD&C Act, the Proteus Personal Monitor including Ingestion Event Marker is subject to the following special controls:
*Classification.* Class II (special controls). The special controls for this device are:(1) The device must be demonstrated to be biocompatible and non-toxic;
(2) Nonclinical, animal, and clinical testing must provide a reasonable assurance of safety and effectiveness, including device performance, durability, compatibility, usability (human factors testing), event recording, and proper excretion of the device;
(3) Appropriate analysis and nonclinical testing must validate electromagnetic compatibility performance, wireless performance, and electrical safety; and
(4) Labeling must include a detailed summary of the nonclinical and clinical testing pertinent to use of the device and the maximum number of daily device ingestions.
Predicate Devices
Proteus® Patch Including Ingestible Sensor (K133263)
Submission Summary (Full Text)
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Public Health Service
Food and Drug Administration 10903 New Hampshire Avenue Document Control Center - WO66-G609 Silver Spring, MD 20993-0002
June 27, 2015
Proteus Digital Health, Inc. Jafar Shenasa Head, Regulatory Affairs 2600 Bridge Parkway, Suite 101 Redwood City, California 94065
Re: K150494
Trade/Device Name: Proteus Digital Health Feedback Device Regulation Number: 21 CFR 880.6305 Regulation Name: Ingestible Event Marker Regulatory Class: Class II Product Code: OZW, DXH Dated: May 22, 2015 Received: May 28, 2015
Dear Jafar Shenasa:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR
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Page 2 - Jafar Shenasa
Part 807); labeling (21 CFR Part 801); medical device reporting (reporting of medical devicerelated adverse events) (21 CFR 803); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820); and if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.
If you desire specific advice for your device on our labeling regulation (21 CFR Part 801), please contact the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to
http://www.fda.gov/MedicalDevices/Safety/ReportaProblem/default.htm for the CDRH's Office of Surveillance and Biometrics/Division of Postmarket Surveillance.
You may obtain other general information on your responsibilities under the Act from the Division of Industry and Consumer Education at its toll-free number (800) 638-2041 or (301) 796-7100 or at its Internet address
http://www.fda.gov/MedicalDevices/ResourcesforYou/Industry/default.htm.
Sincerely yours,
Mitchell Stein
for Bram D. Zuckerman, M.D. Director Division of Cardiovascular Devices Office of Device Evaluation Center for Devices and Radiological Health
Enclosure
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# Indications for Use Statement
# 510(k) Number (if known)
Device Name Proteus® Digital Health Feedback Device
The Proteus® Digital Health Feedback Device consists of a Indications for Use miniaturized, wearable sensor for ambulatory recording of physiological and behavioral metrics such as heart rate, activity, body angle relative to gravity (body position), and time-stamped patientlogged events, including events signaled by the co-incidence with, or co-ingestion with, the ingestible sensor accessory. When the ingestible sensor is ingested, the Proteus Digital Health Feedback Device is intended to log, track and trend intake times. When co-ingested with medication, the tracking and trending of intake times may be used as an aid to measure medication adherence. The Proteus Digital Health Feedback Device may be used in any instance where quantifiable analysis of event-associated physiological and behavioral metrics is desirable, and enables unattended data collection for clinical and research applications.
| Prescription Use X<br>(Per 21 CFR 801.109) | OR | Over-the-Counter Use |
|--------------------------------------------|----|----------------------|
|--------------------------------------------|----|----------------------|
PLEASE DO NOT WRITE BELOW THIS LINE - CONTINUE ON ANOTHER PAGE IF NEEDED
Concurrence of CDRH, Office of Device Evaluation (ODE)
Proteus Digital Health, Inc.
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### 510(k) Summary
Submitted by: Address:
Telephone: Facsimile:
Contact Name:
Proteus Digital Health Inc. 2600 Bridge Parkway, Suite 101 Redwood City, CA, 94065 (650) 637-6230 (650) 362-1860
Arezou Azar, PhD aazar(a)proteus.com
Date Submitted:
May22, 2015
Name of Device
Trade name: Common name: Classification name: Product Code: Subsequent Codes:
Proteus® Digital Health Feedback Device Ingestible Event Marker Ingestible Event Marker (21 CFR 880.6305) OZW DXH
#### Predicate Device
. Proteus® Patch Including Ingestible Sensor (K133263)
### General Device Description
The Proteus Digital Health Feedback Device consists of a wearable sensor, an ingestible sensor, and a software application.
The Proteus wearable sensor is a body-worn sensor that collects physiological and behavioral metrics such as heart rate, activity, body angle relative to gravity (body position), skin temperature, and time-stamped user-logged events signaled by the co-incidence with, or coingestion with, the Proteus ingestible sensor. The display application of the Proteus Digital Health Feedback Device may be used to analyze circadian rhythms and patterns.
The ingestible sensor is embedded inside an inactive tablet. (the Proteus Pill or sensorenabled pill) for ease of handling and swallowing. After the ingestible sensor reaches the stomach, it activates and communicates its presence with a unique identifier to the wearable sensor. When the ingestible sensor is co-ingested with medication, the Proteus device is intended to log, track, and trend medicine intake times as an aid to measure medication adherence.
Proteus Digital Health, Inc.
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The software application receives the data from the wearable sensor for further processing and analysis of the physiological and behavioral metrics. The processed data is then sent to the user interface (UI) for display as well as to Proteus databases for storage and sharing.
#### Intended Use
The Proteus® Digital Health Feedback Device consists of a miniaturized, wearable sensor for ambulatory recording of physiological and behavioral metrics such as heart rate, activity, body angle relative to gravity (body position), and time-stamped patient-logged events, including events signaled by the co-incidence with, or co-ingestion with, the ingestible sensor accessory. When the ingestible sensor is ingested, the Proteus Digital Health Feedback Device is intended to log, track and trend intake times. When co-ingested with medication, the tracking and trending of intake times may be used as an aid to measure medication adherence. The Proteus Digital Health Feedback Device may be used in any instance where quantifiable analysis of event-associated physiological and behavioral metrics is desirable, and enables unattended data collection for clinical and research applications.
| Parameter | Values | |
|----------------------------|---------------------------------------|---------------------------------------|
| | The Wearable Sensor | |
| | One Piece | Two Piece |
| Shape | Ovoid | Rectangular |
| Size | 102mm x 60mm x<br>9.8mm | 98mm x 42mm x<br>11mm |
| Weight | 11 grams | 16 grams |
| Battery Type | Lithium Manganese<br>(LiMn) Coin Cell | Lithium Manganese<br>(LiMn) Coin Cell |
| Moisture<br>Susceptibility | Water-Resistant | Water-Resistant |
| Memory | 4 MB | 16 MB |
| Storage<br>Temperature | Room Temperature | Room Temperature |
| Relative Humidity | Ambient | Ambient |
| | The Pill | |
| Shape | Round | |
| Size | 6.5mm x 2.0mm | |
| Weight | 80mg | |
## Physical Characteristics
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## Technological Characteristics
The technological characteristics of the current device are identical to the predicate device.
| Parameter | Sensor Technology | Method |
|-------------------------|------------------------------------------------|-----------------------------------------------------|
| Heart rate | Biopotential low-frequency<br>amplifier | Digitized R wave |
| Activity | Accelerometer | Digitized accelerometer output |
| Body Angle | Accelerometer | Double integration of<br>accelerometer output |
| Skin Temperature | Thermistor | Digitized voltage from small<br>auxiliary current |
| Manual Event Logging | Patient activated button | Digital pulse |
| Inter-Electrode | Biopotential high-frequency<br>amplifier | Digitized impedance from small<br>auxiliary current |
| Impedance | | |
| Ingestible Event Marker | Bio-galvanically powered<br>ingestible circuit | Volume conduction<br>communication |
## Summary of Non-Clinical Performance Data
The three-axis accelerometer provided motion and angle relative to gravity (body position) data and was validated against a known acceleration applied against each of its three axes.
The biopotential low-frequency amplifier was used to quantify heart rate by measuring Rwave frequency based upon a proprietary algorithm, tested using selected guidelines set forth in the ANSI/AAMI EC 13 standard.
The thermistor provided local skin environment temperature. A small current was applied across the thermistor, and the difference in voltage was quantifed and compared to a reference resistor.
The ingestible sensor was tested for activation time and lifetime after activation.
## Summary of Clinical Performance Data
No additional clinical data were required to confirm substantial equivalence to predicate devices.
### Conclusion
Based on technological characteristics, risk evaluation, and design verification of the Proteus Digital Health Feedback Device, Proteus Digital Health believes that the product is safe and effective, and is substantially equivalent to its predicate device.
Proteus Digital Health, Inc.
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.
