Oliver Amft mostly deals with Activity recognition, Wearable computer, Computer vision, Artificial intelligence and Real-time computing. His biological study spans a wide range of topics, including Ubiquitous computing and Conductive textile. His work on Inertial measurement unit as part of general Computer vision study is frequently linked to Upper body, Resistance response and Strain sensor, bridging the gap between disciplines.
His Inertial measurement unit research incorporates themes from Spotting, Gesture, Gesture recognition and Speech recognition, Hidden Markov model. His work in the fields of Artificial intelligence, such as Classification rate and Benchmark, intersects with other areas such as Clothing industry and Work. His Real-time computing study integrates concerns from other disciplines, such as Range, Simulation, Energy expenditure and Activity classification.
Oliver Amft mainly focuses on Wearable computer, Artificial intelligence, Activity recognition, Simulation and Human–computer interaction. His work deals with themes such as Ubiquitous computing, Speech recognition, Energy expenditure and Mobile computing, which intersect with Wearable computer. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Computer vision and Pattern recognition.
In his study, Energy is strongly linked to Real-time computing, which falls under the umbrella field of Activity recognition. His Human–computer interaction research is multidisciplinary, relying on both Context awareness and Embedded system. His studies deal with areas such as Inertial measurement unit and Gesture as well as Hidden Markov model.
His primary scientific interests are in Wearable computer, Ubiquitous computing, Artificial intelligence, Human–computer interaction and Physical medicine and rehabilitation. Oliver Amft works mostly in the field of Wearable computer, limiting it down to topics relating to Motion sensors and, in certain cases, Feature extraction, as a part of the same area of interest. His study explores the link between Ubiquitous computing and topics such as Wearable technology that cross with problems in E-textiles and Flexible electronics.
His Artificial intelligence research is mostly focused on the topic Spotting. His Human–computer interaction research includes themes of Wearable sensing and Set. His work in Pattern recognition addresses subjects such as Gesture, which are connected to disciplines such as Inertial measurement unit.
Oliver Amft spends much of his time researching Wearable computer, Human–computer interaction, Wearable sensing, Ubiquitous computing and Dietary monitoring. His Wearable computer research is multidisciplinary, incorporating elements of Event and Internet privacy. His Human–computer interaction study frequently involves adjacent topics like Human body.
The various areas that Oliver Amft examines in his Ubiquitous computing study include Information privacy and Medical services. There are a combination of areas like Mastication, Surgery, Audiology, Monitoring ambulatory and Natural food integrated together with his Dietary monitoring study.
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Gesture spotting with body-worn inertial sensors to detect user activities
Holger Junker;Oliver Amft;Paul Lukowicz;Gerhard Tröster.
Pattern Recognition (2008)
Best practice for motor imagery: a systematic literature review on motor imagery training elements in five different disciplines
Corina Schuster;Roger Hilfiker;Oliver Amft;Anne Scheidhauer.
BMC Medicine (2011)
Recognition of dietary activity events using on-body sensors
Oliver Amft;Gerhard Tröster.
Artificial Intelligence in Medicine (2008)
Analysis of chewing sounds for dietary monitoring
Oliver Amft;Mathias Stäger;Paul Lukowicz;Gerhard Tröster.
ubiquitous computing (2005)
Detection of eating and drinking arm gestures using inertial body-worn sensors
O. Amft;H. Junker;G. Troster.
international symposium on wearable computers (2005)
Recognizing Upper Body Postures using Textile Strain Sensors
C. Mattmann;O. Amft;H. Harms;G. Troster.
international symposium on wearable computers (2007)
Advanced internet of things for personalised healthcare systems
Jun Qi;Po Yang;Geyong Min;Oliver Amft.
Pervasive and Mobile Computing (2017)
On-Body Sensing Solutions for Automatic Dietary Monitoring
O. Amft;G. Troster.
IEEE Pervasive Computing (2009)
Rapid Prototyping of Activity Recognition Applications
D. Bannach;P. Lukowicz;O. Amft.
IEEE Pervasive Computing (2008)
Active capacitive sensing: exploring a new wearable sensing modality for activity recognition
Jingyuan Cheng;Oliver Amft;Paul Lukowicz.
international conference on pervasive computing (2010)
Profile was last updated on December 6th, 2021.
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