Defining Adherence: Making Sense of Physical Activity Tracker Data

Author(s): Lie Ming TangJochen MeyerDaniel A. EpsteinKevin BraggLina Engelen Abstract: Increasingly, people are collecting detailed personal activity data from commercial trackers. Such data should be able to give important insights about their activity levels....

Wearable and Implantable Sensors for Biomedical Applications

Author(s): Koydemir, Hatice CeylanOzcan, Aydogan Abstract: Mobile health technologies offer great promise for reducing healthcare costs and improving patient care. Wearable and implantable technologies are contributing to a transformation in the mobile health era in...

Co-evolving with self-tracking technologies

Author: Kristensen, Dorthe Brogård Ruckenstein, Minna Abstract: Seen in a longitudinal perspective, Quantified Self-inspired self-tracking sets up “a laboratory of the self,” where people co-evolve with technologies. By exploring ways in which self-tracking...

The Quantified Relationship

Author(s): Danaher, JohnNyholm, SvenEarp, Brian D. Abstract: The growth of self-tracking and personal surveillance has given rise to the Quantified Self movement. Members of this movement seek to enhance their personal well-being, productivity, and self-actualization...

Data anxieties: Finding trust in everyday digital mess

Author(s): Horst, HeatherLanzeni, DeboraPink, Sarah Abstract: Digital data is an increasing and continual presence across the sites, activities and relationships of everyday life. In this article we explore what data presence means for the ways that the everyday is...

A New Backpropagation Algorithm without Gradient Descent

Author(s): Ranganathan, VarunNatarajan, S. Abstract: The backpropagation algorithm, which had been originally introduced in the 1970s, is the workhorse of learning in neural networks. This backpropagation algorithm makes use of the famous machine learning algorithm...

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