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Modifica Date Corso: Guglielmo Cola - Dipartimento di Ingegneria dell’Informazione, Università di Pisa - "Continuous monitoring of health and well-being using wearable sensors", 14-16 May 2018

Hours:
12 hours (3 credits)

Room:
14 maggio 2018: Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Largo Lucio Lazzarino, Pisa – Piano 6
15 e 16 maggio 2018: Aula Riunioni del Dipartimento di Ingegneria dell’Informazione, Via G. Caruso 16, Pisa – Piano Terra

Short Abstract:
The last years have witnessed a considerable growth in the market of wearable technology. Smart devices, like smartwatches and fitness trackers, embed a wide range of sensors and are potentially worn continuously throughout the day. This scenario has brought about the unprecedented opportunity to constantly monitor users' movements. In turn, this massive amount of information has led to an increasing interest in the development of applications related to health and well-being. In this context, a key challenge is represented by the reliable extraction of relevant patterns from collected signals. For instance, gait analysis applications should devise appropriate signal processing techniques to detect walking activity as well as to analyze and classify gait patterns.

In this course, students will be given a practical glimpse into the emerging field of human activity monitoring by means of wearable sensors. This will include a description of the most relevant signal processing methodologies aimed at achieving accurate and unobtrusive wearable systems.

Course Contents in brief:

  • Introduction to wearable-based systems for continuous monitoring of human activities
    • Applications
    • Devices and sensors
    • System design
  • Fall detection systems
    • Acceleration-based detection of potential falls
    • Pattern recognition techniques to discriminate falls from normal activities
  • Gait detection and analysis
    • Lightweight and reliable detection of gait cycles using wearable systems
    • Gait pattern analysis using supervised learning or anomaly detection
      • Gait-based monitoring of medical conditions
      • Gait as a biometric feature
  • Design and implementation on wearable systems with constrained resources

Schedule:

  • 14/05/2018: 9:30 - 13:30, Largo Lucio Lazzarino
  • 15/05/2018: 9:30 - 13:30, Via Caruso
  • 16/05/2018: 9:30 - 13:30, Via Caruso