252-0312-00L Mobile Health and Activity Monitoring
| Semester | Spring Semester 2023 |
| Lecturers | C. Holz |
| Periodicity | yearly recurring course |
| Language of instruction | English |
Courses
| Number | Title | Hours | Lecturers | ||||
|---|---|---|---|---|---|---|---|
| 252-0312-00 V | Mobile Health and Activity Monitoring TA-Meeting: Monday 13-14, CAB G57 (from 13 March onwards) | 2 hrs |
| C. Holz | |||
| 252-0312-00 A | Mobile Health and Activity Monitoring | 3 hrs | C. Holz |
Catalogue data
| Abstract | Health and activity monitoring has become a key purpose of mobile & wearable devices, e.g., phones, watches, and rings. We will cover the phenomena they capture, i.e., user behavior, actions, and human physiology, as well as the sensors, signals, and methods for processing and analysis. For the exercise, students will receive a wristband to stream and analyze activity and health signals. | |||||||||||||||||||||||||||||||||
| Learning objective | The course will combine high-level concepts with low-level technical methods needed to sense, detect, and understand them. High-level: – sensing modalities for interactive systems – "activities" and "events" (exercises and other mechanical activities such as movements and resulting vibrations) – health monitoring (basic cardiovascular physiology) – affective computing (emotions, mood, personality) Lower-level: – sampling and filtering, time and frequency domains – cross-modal sensor systems, signal synchronization and correlation – event detection, classification, prediction using basic signal processing as well as learning-based methods – sensor types: optical, mechanical/acoustic, electromagnetic | |||||||||||||||||||||||||||||||||
| Content | Health and activity monitoring has become a key purpose of mobile and wearable devices, including phones, (smart) watches, (smart) rings, (smart) belts, and other trackers (e.g., shoe clips, pendants). In this course, we will cover the fundamental aspects that these devices observe, i.e., user behavior, actions, and physiological dynamics of the human body, as well as the sensors, signals, and methods to capture, process, and analyze them. We will then cover methods for pattern extraction and classification on such data. The course will therefore touch on aspects of human activities, cardiovascular and pulmonary physiology, affective computing (recognizing, interpreting, and processing emotions), corresponding lower-level sensing systems (e.g., inertial sensing, optical sensing, photoplethysmography, eletrodermal activity, electrocardiograms) and higher-level computer vision-based sensing (facial expressions, motions, gestures), as well as processing methods for these types of data. The course will be accompanied by a group exercise project, in which students will apply the concepts and methods taught in class. Students will receive a wearable wristband device that streams IMU data to a mobile phone (code will be provided for receiving, storing, visualizing on the phone). Throughout the course and exercises, we will collect data of various human activities from the band, annotate them, analyze, classify, and interpret them. For this, existing and novel processing methods will be developed (plenty of related work exists), based on the collected data as well as existing datasets. We will also combine the band with signals obtained from the mobile phone to holistically capture and analyze health and activity data. Full details: https://teaching.siplab.org/mobile_health_activity_monitoring/2023/ Note: All lectures will be streamed live and recorded for later replay. Hybrid participation will be possible. | |||||||||||||||||||||||||||||||||
| Lecture notes | Copies of slides will be made available Lectures will be streamed live as well as recorded and made available online. More information on the course site: https://teaching.siplab.org/mobile_health_activity_monitoring/2023/ Note: All lectures will be streamed live and recorded for later replay. Hybrid participation will be possible. | |||||||||||||||||||||||||||||||||
| Literature | Will be provided in the lecture | |||||||||||||||||||||||||||||||||
Competencies |
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Performance assessment
| Performance assessment information (valid until the course unit is held again) | |
Performance assessment as a semester course | |
| ECTS credits | 6 credits |
| Examiners | C. Holz |
| Type | end-of-semester examination |
| Language of examination | English |
| Repetition | The performance assessment is only offered at the end after the course unit. Repetition only possible after re-enrolling. |
| Mode of examination | written 90 minutes |
| Additional information on mode of examination | The end-of-term exam will be a computer-based presence exam at ETH facilities. The exam platform will be Moodle. The exam will count 50% of the final grade. The practical exercise counts for the remaining 50% of the final grade. The exercise assignment is mandatory and will need to be submitted on time during the term. |
| Written aids | One handwritten two-sided A4 sheet and a non-programmable calculator. |
| Digital exam | The exam takes place on devices provided by ETH Zurich. |
Learning materials
| Main link | Information |
| Only public learning materials are listed. | |
Groups
| No information on groups available. |
Restrictions
| There are no additional restrictions for the registration. |