Turning the Mobile Phone's Headset Port into a Universal Data Acquisition Interface - Embedded.com

Turning the Mobile Phone’s Headset Port into a Universal Data Acquisition Interface

Mobile phones have become ubiquitous in modern life and they provide many of the features that made personalcomputers popular, but in a compact form-factor, untethered to power, and always networked. Considerable research over the past decade has transformed the mobile phone into a platform that supports continuous sensing applications.

Although many sensors – like accelerometers, gyroscopes, and imagers – have been integrated into the phone, many other sensors – like EKG, air quality, and soil moisture – have not.The desire to support such sensors, coupled with a limited set of direct-connect interfaces suitable for powering external peripherals and transferring data to and from them, have led some to search for a universal peripheral interface port.

One candidate for such a peripheral interface is the mobilephone’s headset port. This interface is mostly standardized,at least physically and somewhat electrically, across many mobile phones, by necessity to ensure compatibility witha broad range of hands-free and headphone audio devices.And, recently introduced peripherals suggest a growing interest in using the headset port for more than just headsets.

For reasons of cost, simplicity, and ubiquity, using the headset port as a general-purpose interface for transferring power and data to peripheral devices is an attractive option. However, there is a considerable variance in the passband characteristics, power delivery ability, signal pin outs,and microphone bias voltage among headset ports on mobile phones.

This leads us to conclude that contrary to recent claims, the headset port is not as universal as one might hope. For example, designs built to work with the iPhone may fail to work on many Android or Windows phones, and vice versa. Furthermore, designs built to work with smartphones may fail to work with the far more numerous but less capable feature phones, making current approaches brittle.The headset port imposes several limitations on mobile phone peripherals.

The power transfer through the headset port is inefficient. Its pass-band characteristics severely limitthe frequency range of passable signals. Features that at firstseem to be of great utility, such as the high sampling rate, andthe ability to create arbitrary waveforms on the output audio channels, turn out to be poorly suited for simple peripherals that do more than essentially capture or playback audio.

We present AudioDAQ, a new platform for continuous data acquisition using the headset port of a mobile phone.AudioDAQ differs from existing phone peripheral interfaces by drawing all necessary power from the microphone bias voltage, encoding all data as analog audio, and leveraging the phone’s built-in voice memo application (or a custom application) for continuous data collection.

Unlike HiJack, it enables sensing applications not just on iOS devices but on smartphones and feature phones. Further, it does not require any hardware/software modifications on the phone. It improves on HiJack by extending the sampling period, a direct result of simplifying the design by trading the flexibility of a microcontroller fora more power-efficient analog solution after recognizing that such a system is adequate for a large class of sensing applications.

These properties make the AudioDAQ design more universal, so it works across a broad range of phones including sophisticated smartphones and simpler feature phones, enables simple analog peripherals without requiring a microcontroller, requires no hardware or software modifications on the phone itself, uses significantly less power than prior approaches, and allows continuous data capture over an extended period of time.

TheAudioDAQ design is efficient because it draws all necessary power from the microphone bias voltage, and it is general because this voltage and a voice memo application are present on most mobile phones in use today. We show the viability of our architecture by evaluating an end-to-end system thatcan capture EKG signals continuously for hours and send thedata to the cloud for storage, processing, and visualization.

To read this external content in full, download the complete paper from the author archives on the University of Michigan website.

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.