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Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Smartphone attachment for stethoscope recording.

Jeff Thompson¹

¹Visual Art and Technology, Stevens Institute of Technology, 1 Castle Point on Hudson, Hoboken, NJ, 07030, USA, mail@jeffreythompson.org.

Methods in Molecular Biology (Clifton, N.J.)

|January 29, 2015

Summary

This summary is machine-generated.

This study presents a 3D-printed iPhone attachment enabling acoustic stethoscope recordings via smartphone. This open-source medical device offers a low-cost solution for on-site diagnostics where specialized equipment is unavailable.

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Area of Science:

Biomedical Engineering
Medical Technology
Open Source Hardware

Background:

Smartphones and 3D printing offer new avenues for developing scientific and medical tools.
Access to specialized medical diagnostic instruments can be limited in certain regions.
Acoustic stethoscopes are common but their audio output is not easily digitized for analysis.

Purpose of the Study:

To design and describe a 3D-printable attachment for smartphones to record acoustic stethoscope sounds.
To facilitate the creation of an accessible, low-cost medical diagnostic tool.
To promote the use of open-source hardware in medical applications.

Main Methods:

A simple attachment was designed for an Apple iPhone using CAD software.
The attachment was fabricated using 3D printing technology.
The device enables the smartphone's microphone to record sound from an acoustic stethoscope.

Main Results:

A functional 3D-printed iPhone attachment was successfully created.
The digital design files are shareable and modifiable for various phones.
The fabricated device is durable and requires no specialized manufacturing equipment.

Conclusions:

The 3D-printed stethoscope attachment provides an affordable method for digital audio recording.
This open-source tool can improve on-site diagnostics in resource-limited settings.
Integration with smartphone applications may enable advanced, automated medical diagnostics.