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(1 - 4 of 4)
- Title
- Wearable Passive Wireless MEMS Respiration Sensor.
- Creator
-
Moradian, Sina, Abdolvand, Reza, Sundaram, Kalpathy, Kapoor, Vikram, University of Central Florida
- Abstract / Description
-
In this study a passive sensor that wirelessly monitors the profile of the human respiratory system is presented. The sensor was designed to be wearable, weighs less than 10 grams and is durable. The sensor is made of a RF piezoelectric MEMS resonator and an ultra-high frequency antenna made of a thin metal film formed on a flexible substrate . The resonance frequency of the TPoS resonator shifts as a function of condensation and evaporation of water vapor on the surface of the resonator and...
Show moreIn this study a passive sensor that wirelessly monitors the profile of the human respiratory system is presented. The sensor was designed to be wearable, weighs less than 10 grams and is durable. The sensor is made of a RF piezoelectric MEMS resonator and an ultra-high frequency antenna made of a thin metal film formed on a flexible substrate . The resonance frequency of the TPoS resonator shifts as a function of condensation and evaporation of water vapor on the surface of the resonator and changes in resonator's temperature. These parameters change in each in response to inspiration and expiration and a wireless measurement system detects the frequency shift of the sensor and converts it into the respiration profile. The respiration profile of a healthy human subject is measured and presented for a transmitter to sensor to receiver distance of ~25cm.
Show less - Date Issued
- 2017
- Identifier
- CFE0006628, ucf:51279
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006628
- Title
- THE EFFECTS OF WEARABLE FITNESS DEVICES ON PEDIATRIC OBESITY: AN INTEGRATIVE LITERATURE REVIEW.
- Creator
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Sabina, Kevin, Decker, Jonathan, Hill, Peggy, University of Central Florida
- Abstract / Description
-
Childhood obesity is a foremost concern throughout the health care community. Approximately 17.6% of the pediatric population meet the criteria for obesity, which can lead to health disparities later in life, such as hypertension, type 2 diabetes mellitus, and metabolic syndrome. Emerging mobile and wearable lifestyle tracking devices can be a viable solution to the challenging problem of childhood obesity through behavior changes, feasibility, and adherence. The purpose of this literature...
Show moreChildhood obesity is a foremost concern throughout the health care community. Approximately 17.6% of the pediatric population meet the criteria for obesity, which can lead to health disparities later in life, such as hypertension, type 2 diabetes mellitus, and metabolic syndrome. Emerging mobile and wearable lifestyle tracking devices can be a viable solution to the challenging problem of childhood obesity through behavior changes, feasibility, and adherence. The purpose of this literature review was to determine the effect that mobile and wearable activity tracking devices have on the obese pediatric population. A centralized review of the literature was conducted using various data basesand resulted in 19 articles. 5 articles were chosen to review in more detail. 13 other articles were hand searched through credible resource citations, rendering 14 articles that met all criteria. The three general themes found in this literature review suggest that wearable activity tracking devices can be designed and effectively used by the pediatric population. Also, wearable activity tracking devices are accurate in conveying information on physical activity, calories, and heart rate. Lastly, wearable activity tracking devices can initiate behavioral changes in children leading to an increase in physical activity, resulting in the prevention and treatment of pediatric obesity.While in a majority of the studies analyzed trails were short. The research suggests wearable activity tracking devices will produce the desired results of increased activity in pediatric populations when they are worn correctly, are adequately engaging, and when they are designed in a feasible manner that is appealing to children.
Show less - Date Issued
- 2018
- Identifier
- CFH2000375, ucf:45824
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000375
- Title
- A WEARABLE HEAD-MOUNTED PROJECTION DISPLAY.
- Creator
-
Martins, Ricardo, Clarke, Thomas, University of Central Florida
- Abstract / Description
-
Conventional head-mounted projection displays (HMPDs) contain of a pair of miniature projection lenses, beamsplitters, and miniature displays mounted on the helmet, as well as a retro-reflective screen placed strategically in the environment. We have extened the HMPD technology integrating the screen into a fully mobile embodiment. Some initial efforts of demonstrating this technology has been captured followed by an investigation of the diffraction effects versus image degradation caused by...
Show moreConventional head-mounted projection displays (HMPDs) contain of a pair of miniature projection lenses, beamsplitters, and miniature displays mounted on the helmet, as well as a retro-reflective screen placed strategically in the environment. We have extened the HMPD technology integrating the screen into a fully mobile embodiment. Some initial efforts of demonstrating this technology has been captured followed by an investigation of the diffraction effects versus image degradation caused by integrating the retro-reflective screen within the HMPD. The key contribution of this research is the conception and development of a mobile-HMPD (M-HMPD). We have included an extensive analysis of macro- and microscopic properties that encompass the retro-reflective screen. Furthermore, an evaluation of the overall performance of the optics will be assessed in both object space for the optical designer and visual space for the possible users of this technology. This research effort will also be focused on conceiving a mobile M-HMPD aimed for dual indoor/outdoor applications. The M-HMPD shares the known advantage such as ultra-lightweight optics (i.e. 8g per eye), unperceptible distortion (i.e. ≤ 2.5%), and lightweight headset (i.e. ≤ 2.5 lbs) compared with eyepiece type head-mounted displays (HMDs) of equal eye relief and field of view. In addition, the M-HMPD also presents an advantage over the preexisting HMPD in that it does not require a retro-reflective screen placed strategically in the environment. This newly developed M-HMPD has the ability to project clear images at three different locations within near- or far-field observation depths without loss of image quality. This particular M-HMPD embodiment was targeted to mixed reality, augmented reality, and wearable display applications.
Show less - Date Issued
- 2010
- Identifier
- CFE0003431, ucf:48390
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003431
- Title
- Spatial and Temporal Modeling for Human Activity Recognition from Multimodal Sequential Data.
- Creator
-
Ye, Jun, Hua, Kien, Foroosh, Hassan, Zou, Changchun, Karwowski, Waldemar, University of Central Florida
- Abstract / Description
-
Human Activity Recognition (HAR) has been an intense research area for more than a decade. Different sensors, ranging from 2D and 3D cameras to accelerometers, gyroscopes, and magnetometers, have been employed to generate multimodal signals to detect various human activities. With the advancement of sensing technology and the popularity of mobile devices, depth cameras and wearable devices, such as Microsoft Kinect and smart wristbands, open a unprecedented opportunity to solve the...
Show moreHuman Activity Recognition (HAR) has been an intense research area for more than a decade. Different sensors, ranging from 2D and 3D cameras to accelerometers, gyroscopes, and magnetometers, have been employed to generate multimodal signals to detect various human activities. With the advancement of sensing technology and the popularity of mobile devices, depth cameras and wearable devices, such as Microsoft Kinect and smart wristbands, open a unprecedented opportunity to solve the challenging HAR problem by learning expressive representations from the multimodal signals recording huge amounts of daily activities which comprise a rich set of categories.Although competitive performance has been reported, existing methods focus on the statistical or spatial representation of the human activity sequence;while the internal temporal dynamics of the human activity sequence arenot sufficiently exploited. As a result, they often face the challenge of recognizing visually similar activities composed of dynamic patterns in different temporal order. In addition, many model-driven methods based on sophisticated features and carefully-designed classifiers are computationally demanding and unable to scale to a large dataset. In this dissertation, we propose to address these challenges from three different perspectives; namely, 3D spatial relationship modeling, dynamic temporal quantization, and temporal order encoding.We propose a novel octree-based algorithm for computing the 3D spatial relationships between objects from a 3D point cloud captured by a Kinect sensor. A set of 26 3D spatial directions are defined to describe the spatial relationship of an object with respect to a reference object. These 3D directions are implemented as a set of spatial operators, such as "AboveSouthEast" and "BelowNorthWest," of an event query language to query human activities in an indoor environment; for example, "A person walks in the hallway from north to south." The performance is quantitatively evaluated in a public RGBD object dataset and qualitatively investigated in a live video computing platform.In order to address the challenge of temporal modeling in human action recognition, we introduce the dynamic temporal quantization, a clustering-like algorithm to quantize human action sequences of varied lengths into fixed-size quantized vectors. A two-step optimization algorithm is proposed to jointly optimize the quantization of the original sequence. In the aggregation step, frames falling into the sample segment are aggregated by max-polling and produce the quantized representation of the segment. During the assignment step, frame-segment assignment is updated according to dynamic time warping, while the temporal order of the entire sequence is preserved. The proposed technique is evaluated on three public 3D human action datasets and achieves state-of-the-art performance.Finally, we propose a novel temporal order encoding approach that models the temporal dynamics of the sequential data for human activity recognition. The algorithm encodes the temporal order of the latent patterns extracted by the subspace projection and generates a highly compact First-Take-All (FTA) feature vector representing the entire sequential data. An optimization algorithm is further introduced to learn the optimized projections in order to increase the discriminative power of the FTA feature. The compactness of the FTA feature makes it extremely efficient for human activity recognition with nearest neighbor search based on Hamming distance. Experimental results on two public human activity datasets demonstrate the advantages of the FTA feature over state-of-the-art methods in both accuracy and efficiency.
Show less - Date Issued
- 2016
- Identifier
- CFE0006516, ucf:51367
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0006516
