Chengliu Li

A Wearable Electronic System for Objective Dietary Assessment

Dietary reporting by individuals is subject to error (1–3). Therefore, a research program has been initiated to develop a small electronic device to record food intake automatically. This device, which contains a miniature camera, a microphone, and several other sensors, can be worn on a lanyard around the neck. It collects visual data immediately in front of the participant and stores them on a memory card in the device. The data are transferred regularly to the dietitian’s computer for further processing and analysis. The device is designed to be almost completely passive to the participant, and thus hopefully will not intrude on or alter the participant’s eating activities. In addition to this function, in the future the device will have other functions, such as the measurement of physical activity, human behavior, and environmental exposure (e.g., pollutants).

Relay Effect of Wireless Power Transfer Using Strongly Coupled Magnetic Resonances

Wireless power transfer using strongly coupled electromagnetic resonators is a recently explored technology. Although this technology is able to transmit electrical energy over a much longer distance than traditional near field methods, in some applications, its effective distance is still insufficient. In this paper, we investigate a relay effect to extend the energy transfer distance. Theoretical analysis is performed based on a set of coupled-mode equations. Experiments are conducted to confirm the theoretical results and demonstrate the effectiveness of the relay approach. Our results show that the efficiency of power transfer can be improved significantly using one or more relay resonators. This approach significantly improves the performance of the present two-resonator system and allows a curved path in space to be defined for wireless power transfer using smaller resonators.

Accuracy of food portion size estimation from digital pictures acquired by a chest-worn camera

OBJECTIVE Accurate estimation of food portion size is of paramount importance in dietary studies. We have developed a small, chest-worn electronic device called eButton which automatically takes pictures of consumed foods for objective dietary assessment. From the acquired pictures, the food portion size can be calculated semi-automatically with the help of computer software. The aim of the present study is to evaluate the accuracy of the calculated food portion size (volumes) from eButton pictures. DESIGN Participants wore an eButton during their lunch. The volume of food in each eButton picture was calculated using software. For comparison, three raters estimated the food volume by viewing the same picture. The actual volume was determined by physical measurement using seed displacement. SETTING Dining room and offices in a research laboratory. SUBJECTS Seven lab member volunteers. RESULTS Images of 100 food samples (fifty Western and fifty Asian foods) were collected and each food volume was estimated from these images using software. The mean relative error between the estimated volume and the actual volume over all the samples was -2·8 % (95 % CI -6·8 %, 1·2 %) with sd of 20·4 %. For eighty-five samples, the food volumes determined by computer differed by no more than 30 % from the results of actual physical measurements. When the volume estimates by the computer and raters were compared, the computer estimates showed much less bias and variability. CONCLUSIONS From the same eButton pictures, the computer-based method provides more objective and accurate estimates of food volume than the visual estimation method.

eButton: A Wearable Computer for Health Monitoring and Personal Assistance

Recent advances in mobile devices have made profound changes in peoples daily lives. In particular, the impact of easy access of information by the smartphone has been tremendous. However, the impact of mobile devices on healthcare has been limited. Diagnosis and treatment of diseases are still initiated by occurrences of symptoms, and technologies and devices that emphasize on disease prevention and early detection outside hospitals are under-developed. Besides healthcare, mobile devices have not yet been designed to fully benefit people with special needs, such as the elderly and those suffering from certain disabilities, such blindness. In this paper, an overview of our research on a new wearable computer called eButton is presented. The concepts of its design and electronic implementation are described. Several applications of the eButton are described, including evaluating diet and physical activity, studying sedentary behavior, assisting the blind and visually impaired people, and monitoring older adults suffering from dementia.

Magnetic hand tracking for human-computer interface

Hand tracking is useful in human-computer interface. In this work, permanent magnets and contactless magnetic sensors are used to track finger motion. A magnet patch is affixed to each fingernail to mark the location of the fingertip. When fingers move, the combined magnetic fields produced by the magnets at fingertips are recorded by a set of magnetic sensors around a wristband. The recorded data are fed to a source localization algorithm to reconstruct the fingertip locations and estimate hand posture.

Designing a wearable computer for lifestyle evaluation

A wearable computer, called eButton, has been developed for evaluation of the human lifestyle. This ARM-based device acquires multimodal data from a camera module, a motion sensor, an orientation sensor, a light sensor and a GPS receiver. Its performance has been tested both in our laboratory and by human subjects in free-living conditions. Our results indicate that eButton can record real-world data reliably, providing a powerful tool for the evaluation of lifestyle for a broad range of applications.

Wireless power delivery for wearable sensors and implants in Body Sensor Networks

A recent study on witricity (wireless electricity) has demonstrated that wireless energy can be delivered over a moderate distance using strongly coupled magnetic resonance. The objective of this work is to apply the witricity technology to the problem of powering a wireless Body Sensor Network (wBSN). The theory of witricity is investigated using coupled mode theory. Compact witricity resonators are designed, and a working prototype of witricity powered wBSN is built and evaluated. An energy transfer efficiency of about 80 % over a distance of 15 cm is achieved. Besides the high efficiency, it has been observed that a certain misalignment between the transmitter and receiver has little effect on the power transfer. Our experimental results indicate that witricity provides a powerful solution to the energy supply problem of wBSN.

Solar cell phone charger performance in indoor environment

Utilization of solar energy as a power source has been one of the most active fields in science and engineering. One of the recent developments is to use a solar panel to recharge a cell phone. In order to validate the feasibility of this promising application, we conducted experiments on solar cell efficiency under the indoor environment using a typical commercial solar panel. Several types of indoor conditions were investigated. Our results indicate that, within sunshine illuminated rooms or under direct light exposure from a lamp, the power requirement for cell phone charging can be satisfied or provided to some extent. However, in the cloudy condition or under normal fluorescent lighting, the solar cell does not produce enough power to charge a cell phone.

Eating Event Detection by Magnetic Proximity Sensing

Eating event detection is an important problem in automatic dietary study using a wearable computer, such as the eButton. In this work, we approach this detection problem based on the use of a small magnet marker attached to a finger and a miniature magnetometer installed within the eButton. Our experimental results indicate that our magnetic approach is effective when the distance between the marker and the wearable computer is within 12cm, and the range of detection is approximately 15cm. We also found that the proximity signal patterns corresponding to eating and other daily activities are different, which can be used to reduce the false detection rate. In addition, our approach is convenient, low-cost and energy efficient, suitable for practical applications.

Food density estimation using fuzzy logic inference

This paper presents a novel application of fuzzy logic inference to food density estimation to support research in nutrition science. French fries are taken as an example of this new application. A fuzzy Inference System (FIS) is constructed to estimate the bulk density of French fries under different cooking conditions. Our experimental results show that our density estimation method is accurate with a mean error of 2.2%.