Instructions for Use

AudibleHealth AI is a Clinical Decision Support Software (CDSS) intended to support healthcare providers in screening for tuberculosis, COVID, and/or pneumonia through the evaluation of a forced cough vocalization. The test is intended for point-of-care use by a healthcare provider to screen adults 18 years of age or older. AudibleHealth AI does not provide a definitive diagnosis and is not intended to be a standalone diagnostic tool. As a CDSS, it is intended for use in conjunction with risk assessment, radiography, and other medical diagnostic evaluations to assist the clinician in making individual patient management decisions.

Use of the AudibleHealth AI device for screening is contraindicated for the following persons:

• Recent acute traumatic injury to the head, neck, throat, chest, abdomen, or trunk
• Patent tracheostomy stoma
• Recent chest/abdomen/trunk trauma or surgery, recent/persistent neurovascular injury, or recent intracranial surgery
• Persons unable to cough voluntarily
• Medical history of cribriform plate injury or cribriform plate surgery, diaphragmatic hernia, external beam neck / throat / maxillofacial radiation, phrenic nerve injury/palsy, radical neck / throat / maxillofacial surgery, vocal cord trauma or nodules
• Persons with aphasia may have difficulty in producing an FCV in the time allotted by the app and have not been evaluated as a population.

Warnings

Precautions

Potential complications / adverse events

Submission of cough samples for analysis by an AI/ML clinical decision support software is a low-risk procedure. Potential complications may occur during or following FCV collection, including but not limited to light-headedness or shortness of breath.

The AudibleHealth AI web app is compatible with the following web browsers: Google Chrome, Safari, Samsung Internet, and Android Chrome, when used on smartphones running iOS (version 18 or newer) and Android (version 13 or newer) operating systems.

The AudibleHealth AI is a clinical decision support software (CDSS) that is comprised of an ensemble of software subroutines using Artificial Intelligence/Machine Learning (AI/ML) to support healthcare providers (HCPs) in screening for illness by evaluating forced cough vocalizations (FCV).

Components of the AudibleHealth AI are as follows:

• One Time Test Web App Module
• Sound Processing Module
• Predictive Engines
• Laboratory Information Management System (LIMS) interface

The One Time Test Web App Module, which is the user interface seen by the end user, allows the end user to submit the audio file using a smartphone.

The Sound Processing module has several components that ensure each FCV is of adequate sound quality and prepares the FCV to be evaluated by the AI/ML models. The first 50ms are trimmed from the beginning of the audio file as they do not provide data that assists in screening. A normalization step is used to scale the value of the signal to a uniform range (-14dBFS) to help with the de-clipping of the samples. If the audio file is in stereo sound (presented through two channels), it is converted to mono (one channel). The high-pass filter removes frequencies below a specific threshold from the file. A second normalization step is then performed to further scale the file to a better range (-6dBFS). Then the FCV passes through the wav2vec splitter, which turns the files into individual segments containing only one cough each. The duration filter ensures the quality of the splits by removing multi-cough segments and segments that are too short to be properly evaluated. If at least ten segmented coughs are usable after the completion of sound processing, the samples will be re-sampled to the sampling rates needed by the algorithm and sent to the AI/ML models. If there are not ten usable coughs, the user is prompted to submit a new FCV sample as described in the cough collection instructions.

The predictive engine consists of an ensemble of AI classifiers and a deterministic oracle. The classifiers are a group of deep convolutional neural networks (CNNs) trained to detect specific disease signatures in the cough sample, which gets converted from an audio file to an extremely data-rich spectrogram image. Another custom piece of software, known as a deterministic oracle, is connected to the ensemble to take in predictions from each CNN and deliver a final predictive score based on the data provided by the CNNs. Respiratory-related illnesses create specific disease signatures or patterns in the thousands of data points collected in each cough sample. This is due to the unique ways in which each disease affects the human respiratory system. Some diseases create additional mucus, cause changes in mucus viscosity, cause varying inflammation and cough harmonics, or produce conditions like airway constriction. By collecting many coughs from subjects who are confirmed positive for a specific disease and many coughs from people who are confirmed negative, AudibleHealth AI data scientists train AI/ML models that detect the specific patterns correlated to the target disease positives or negatives. After the CNN classifiers and the accompanying oracle have been trained and tested on a sufficient number of positive and negative samples, the predictive engine is capable of evaluating a new cough to determine whether the cough pattern matches the known signature for the target illness. For each illness, a separate ensemble of AI/ML models with their own accompanying oracle is trained, tested, and deployed. Each time the solution is used, the provider receives a numeric probability score between 0 and 100, indicating the likelihood that the sample does or does not correlate to the known disease being screened, with scores over 50 being considered positive and scores below 50 being negative. Each predictive engine algorithm used for screening is a locked ML solution that is not continuously learning while in live production.

The LIMS interface is a laboratory industry-standard data transfer protocol for reporting and recording test results.

Device packaging or presentation

The user interface for this device is offered as a web application (app) for Android version 13 through the current version and iOS version 18 through the current version. The app is the only packaging for this device. To use the app, a healthcare provider must send a link to the user's phone. Once the link is selected, the web app will open automatically. This web app is only available as a point-of-care-use product. Only healthcare providers and organizations with appropriate credentials may prescribe this app for screening.

Although the software cannot become contaminated itself, submission of a cough requires the user to cough in their environment. Since coughing is one of the most common ways respiratory illnesses spread from person to person, utilizing high-quality infection control procedures is a key safety consideration when using AudibleHealth AI. First and foremost, follow facility protocol for disinfecting equipment. If there is no facility protocol or a patient is using a personal smartphone, here are some recommendations to assist in infection control:

• Ensure that the patient and healthcare workers wear an N95 quality mask during cough collection where appropriate.
• Where possible, providing a special cough collection location that is separated from others if indoors, or ideally is located outdoors.
• Thoroughly wipe down any devices used for cough collection or surfaces that may have been exposed to droplets or aerosolized particles with disposable, anti-bacterial, alcohol-based wipes. This includes smartphones as well as other medical equipment, supplies, etc., where appropriate.
• Use a UV light sanitizing tray to decontaminate phones and tablets by placing the device in the decontamination tray for several minutes. These devices are clinically proven to eliminate 99% of bacteria, even in the tiny spaces and crevices found in phones and tablets.
• Ensuring that the healthcare or community health worker wears disposable gloves and changes them between patients in case any particles are transferred

You will receive a screening result for each screener type you have selected within the system where the screener was ordered. Screening Results are presented as (1) High Risk, meaning that the chance the patient has the specified illness is 50% or greater, or (2) Low Risk, meaning that the chance the patient has the specified illness is less than 50%. The probability of illness is also displayed for reference.

In the most recent clinical study, the performance of the CDSS was as follows:

Results are for screening for pulmonary tuberculosis infection in individuals who are symptomatic with a cough, COVID-19 illness, or pneumonia. High risk results are indicative of forced cough vocalization associated with the presence of the specified illness. Clinical correlation with patient history and other diagnostic information is necessary to determine the patient's infection status. High risk screening results do not rule out the possibility of co-infection with other bacteria or viruses (including other screener types offered that may not have been selected).

Test results for reportable diseases will be reported to the appropriate public health authorities by AudibleHealth AI, Inc., in accordance with local, state, and federal requirements.

• The link you send to your patient expires after 14 days (or a shorter timeframe if requested by your administrator). If the patient attempts to access an expired link, a screen will appear in the web browser, noting the expiration. The patient will have the option to request a new link. You will be able to view the request in the system you use to send tests (as noted in Sending a Test).
• The link will also expire as soon as it is used. If the patient attempts to access a link that has already been used, a screen will appear in the web browser, noting that the link has been used. The patient will NOT have an option to send a further request through the system if this occurs.

Screen 1 of 4 · swipe to see more

Security requirements

• Minimum mobile operating system requirements - Android 13 or higher in mobile and iOS 18 or higher in mobile with a mobile browser (Android, Chrome, Samsung Internet, or Safari)
• Regardless of mobile device, users should have the latest available security patches, up-to-date operating system software, and browser software as made available via the auto-update
• Secure 4G, 5G, or Wi-fi access network to the Internet (i.e., not public Wi-fi)
• Minimum bandwidth (512 kbps of upload and download)
• Working microphone

Additional security recommendations

Our application currently does not require geolocation; if requested, do not accept it. As a general practice, users should ensure their devices are not compromised.

• Do not use a jailbroken device.
• Ensure your device is free from virus or malware infection.
• We recommend using the internet more privately with iCloud Private Relay or a personal VPN connection.
• Use Safety Check software to determine compromised passwords or devices.
• Protect access to your device with biometric access (ex., Apple Face ID or a Strong Passcode) to access your device and your browser.
• If you find your iPhone or Android device and personal accounts are targeted by sophisticated remote attacks (targeted by some of the most sophisticated digital threats, such as those from private companies developing state-sponsored mercenary spyware) protect yourself with Lockdown Mode on your mobile device.

This is governed by the law of the nation in which it is marketed (requirements and symbols may vary across countries and jurisdictions). Below are the pictures and their definitions, as they appear on the device label and packaging.

Symbol	Meaning	Reference
	Manufacturer	ISO 15223-1, 5.1.1
	Translation	ISO 15223-1, 5.7.8

App icon:

AudibleHealth AI app icon

Warranty

No warranty, actual or implied, is offered for the AudibleHealth AI.

Manufacturer

This product is manufactured by: AudibleHealth AI, Inc.

6400 S. Fiddlers Green Circle, Suite 250 Greenwood Village, Colorado 80111 USA

Contact: https://help.audiblehealth.ai/

GS1: 00199284438224 GMDN: 64033