Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 101 for “"Activity recognition"”.
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Change detection for activity recognition.
Activity Recognition is concerned with identifying the physical state of a user at a particular point in time. Activity recognition task requires the training of classification algorithm using the processed sensor data from the representative population of users. The accuracy of the generated model …
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Human Activity Recognition using Hearing Aids
As people age, monitoring physical activity becomes increasingly important for assessing and maintaining health. Wearable devices are a promising means of accomplishing this measurement since they are unobtrusive, portable, and accessible. This thesis investigates the feasibility of using hearing …
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Activity Recognition using Singular Value Decomposition
… of a wearable system to record context such as activity recognition is influenced by a combination of variables. A flexible yet systematic approach for building a software classification environment according to a set of variables is described. The integral part of the software design is the use …
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Context-aware activity recognition using TAN classifiers
Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
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Planetary navigation activity recognition using wearable accelerometer data
Activity recognition can be an important part of human health awareness. Many benefits can be generated from the recognition results, including knowledge of activity intensity as it relates to wellness over time. Various activity-recognition techniques have been presented in the literature, though …
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The role of representations in human activity recognition
… role of representations in sensor based human activity recognition (HAR). In particular, we develop convolutional and recurrent autoencoder architectures for feature learning and compare their performance to a distribution-based representation as well as a supervised deep learning …
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Device-Free WiFi Sensing for Human Activity Recognition
Human activity recognition (HAR) using WiFi signals (WiFi-based HAR) has drawn considerable interest from the research community. In contrast to traditional device-based sensing techniques, WiFi-based HAR possesses several advantages, including convenience, wide availability, and privacy …
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A Pervasive Middleware for Activity Recognition with Smartphones
Activity Recognition (AR) is an important research topic in pervasive computing. With the rapid increase in the use of pervasive devices, huge sensor data is generated from diverse devices on a daily basis. Analysis of the sensor data is a significant area of research for AR. There are several …
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Activity recognition based on thermopile imaging array sensors
1 PDF file (vii, 70 pages)
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Multi-sensor activity recognition of an elderly person.
… and insufficient and ineffective care. Activity recognition can be used as the key part of the intelligent sys- tems to allow elderly people to live independently at homes, reduce care cost and burden to the caregivers, provide assurance for the fam- ilies, and promote better care. …
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Self-supervised Learning for IMU-based Human Activity Recognition
In recent years, human activity recognition has drawn considerable attention due to its application in a variety of areas such as smart homes and health. The pervasiveness of wearable devices and smartphones has provided many research opportunities for human activity recognition using inertial …
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Compensating for On-Body Placement Effects in Activity Recognition
… sensors integrated in those devices for context recognition. The vast majority of context recognition research assumes well defined, fixed sen- sor locations. Although this might be acceptable for some application domains (e.g. in an industrial setting), users, in general, will have a hard time …
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Human activity recognition and gymnastics analysis through depth imagery
… many areas of computer vision, such as object recognition, human detection, human activity recognition, and sports analysis. The goal of my work is twofold: (1) use depth imagery to effectively analyze the pommel horse event in men’s gymnastics, and (2) explore and build upon the use of depth …
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Unsupervised video segmentation and its application to activity recognition
… problem of computer vision: segmentation and recognition, in the space-time domain. With the knowledge that generic image segmentation introduces unstable regions due to illumination, com- pression, etc., we utilized temporal information to achieve consistent 3D video segmentation. By …
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Self-supervised learning for data-efficient human activity recognition
… user behaviours. Within mobile sensing, human activity recognition is a fundamental task that aims to identify users' physical actions. Motivated by advancements in deep learning, human activity recognition research has also widely adopted these methods. However, compared to other data …
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End-user modification and correction of home activity recognition
… but the decision processes involved in this recognition are too complex for the end-users of the home to understand. Even at 90% accuracy, errors are inevitable and frequent, and when they do occur the end-users have no tools to understand the cause of errors or to correct them. Instead of …
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Activity Recognition Processing in a Self-Contained Wearable System
… components geared towards the application of activity recognition. An activity recogni tion system built into a wearable textile substrate can be utilized in a variety of areas including health monitoring, military applications, entertainment, and fashion. Many of the activity recognition and …
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NEURO-SYMBOLIC AI APPROACHES FOR SENSOR-BASED HUMAN ACTIVITY RECOGNITION
Sensor-based Human Activity Recognition (HAR) is an active research area, with relevant applications in healthcare and well-being. Deep Learning (DL) classifiers are currently the leading approach to tackle HAR, but their deployment is often limited by their inherent opacity and the scarcity of …
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