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                <h1 class="title">Oxford Step Counter</h1>
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                        <h1>About the project</h1>
                        <p>The Oxford Step Counter is a project developed by Jamieson Brynes during his fourth-year research project at the University of Oxford</p>
                        <p>The algorithm that analyses the accelerometer signal in order to estimate the number of steps is inspired by [1] and better described in our new paper [2].</p>

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                        <h2>The code</h2>
                        <p>These repositories provide access to the code and the data gathered during the project.</p>
                        <ul>
                        	<li><a href="https://github.com/Oxford-step-counter/Java-Step-Counter">Java-Step-Counter</a> contains the algorithm implementation for Java and Android</li>
				<li><a href="https://github.com/Oxford-step-counter/C-Step-Counter">C-Step-Counter</a> contains the algorithm ported to C for embedded devices</li>
				<li><a href="https://github.com/Oxford-step-counter/Step-Counter-Android-Example-App">Step-Counter-Android-Example-App</a> is an Android app that shows how to use the step counter algorithm and logs raw data on CSV files</li>
				<li><a href="https://github.com/Oxford-step-counter/DataSet">DataSet</a> contains the dataset used for optimising the algorithm and for validating it</li>
				<li><a href="https://github.com/Oxford-step-counter/Step-Counting-Algorithms-Testing">Step-Counting-Algorithms-Testing</a> provides python code to optimise the parameters of the algorithm</li>
				<li><a href="https://github.com/Oxford-step-counter/Data-Collection-Android-App">Data-Collection-Android-App</a> is an app used to collect raw accelerometry and ground truth</li>
				<li><a href="https://github.com/Oxford-step-counter/GroundTruthDevice">GroundTruthDevice</a> contains the source code for a device to collect "ground truth" step counting using an RFduino</li>
				<li><a href="https://github.com/Oxford-step-counter/report">report</a> is the project report</li>
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                        <h3>References</h3>
						<ol>
							<li>Brajdic, Agata, and Robert Harle. "Walk detection and step counting on unconstrained smartphones." Proceedings of the 2013 ACM international joint conference on Pervasive and ubiquitous computing. ACM, 2013.</li>
							<li>Salvi, Dario, Carmelo Velardo, Jamieson Brynes, and Lionel Tarassenko. "An optimised algorithm for accurate steps counting from smart-phone accelerometry." In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 4423-4427. IEEE, 2018.</li>
							<li>Anna Brondin, Marcus Nordström, Carl Magnus Olsson, and Dario Salvi. 2020. Open source step counter algorithm for wearable devices. In <i>10th International Conference on the Internet of Things Companion</i> (<i>IoT '20 Companion</i>). Association for Computing Machinery, New York, NY, USA, Article 6, 1–7. DOI:https://doi.org/10.1145/3423423.3423431</li>
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                <h3>Biomedical Signal Processing &amp; m-Health - Institute of Biomedical Engineering</h3>
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