Carlos Oppus

A study on ocular and facial muscle artifacts in EEG signals for BCI applications

This work aims to analyze the EEG signals produced by facial gestures and eye movements called artifacts. Although these signals are considered contaminants in EEG signals used for medical diagnosis, these are observed in order to consider the possibility of using them as inputs for certain applications. As such, the project aims to observe distinct signal patterns in the EEG signals acquired for certain facial gestures as a preliminary work to facial gesture detection. Using the Emotiv Epoc Neuroheadset, the cross correlation between pairs of 14 channels for six facial gestures and their frequency response are compared. These facial gestures are blink, left wink, right wink, raise brow, smile, and clench. Particular channel pairs are found to be highly correlated for certain facial gestures and can be used as possible means of detecting these gestures. In the frequency domain, only the gestures smile and clench registered a distinctive frequency response among the other gestures. Moreover, the Emotiv Epoc neuroheadset paired with the Arduino Duemilanove board was found to be an effective tool as a controller for household appliances. Also, the neuroheadset was useful in developing an extended communication platform. As such not only does it prove to be a viable device for developing systems in aiding the physically-challenged, but also provides a glimpse of the potential advances in the field of Brain-Computer Interfaces.

An agricultural telemetry system implemented using an Arduino-Android interface

The research aims to create a wireless telemetry system to be used in the field of agriculture. The Arduino microprocessor was used in conjunction with sensors to measure environmental factors namely the temperature, humidity and soil moisture. Two methods were created in storing the data in the database. The first method is a more direct approach and is limited to scenarios when Wi-Fi connection is available. Data is sent directly to the server via Wi-Fi, The second approach is used when Wi-Fi is not available since data is sent to another android phone via SMS. The second android phone is responsible for sending data to the database. The data collected were compared with actual sensors and past data recorded by PAGASA to test for the accuracy of the system. The identification of each plant could easily be verified since a certain code was attached for each sample. The latitude, longitude and pictures of the samples were recorded in the database via the methods described above.

User-oriented finger-gesture glove controller with hand movement virtualization using flex sensors and a digital accelerometer

A low-cost wireless glove controller that detects finger gestures was developed using makeshift flex sensors and a digital accelerometer. The performance of the makeshift flex sensors was compared to that of commercially available ones. A system using Arduino, Bluetooth, and Processing was developed to allow the user to specify desired finger gestures for controlling a variety of robotic devices. A simple mobile robot (mobot) was used to demonstrate the capabilities of the glove in controlling devices. A 3D virtual environment was also created for the virtualization of the users hand movements detected by the glove controller. Inside this virtual environment, the user-defined finger gestures also allowed the user to control elements inside the virtual environment which can branch out to various applications including rehabilitation and body-oriented gaming.

Prolonged distraction testing game implemented with ImpactJS HTML5, Gamepad and Neurosky

This research aims to let people know their hierarchy of prolonged distractions starting from the most distracting to the least distracting factors while driving a car. In order to do this, an HTML5 game that simulated a car drive with numerous distractions, which include both audio and visual distractions, was created. The player of the game needs to wear an EEG device, Neurosky, for his or her Beta waves to be detected and collected. The collected Beta waves are then passed to the HTML5 game for processing. This process correlated prolonged distractions with their respective hierarchical position for the player. Once the player receives his/her respective hierarchy of prolonged distractions, he/she will be able to improve and even learn to avoid certain distractions.

FPGA-Based Digital Signal Processing Trainer

Field programmable gate arrays (FPGAs) have been used in a wide range of applications including the field of digital signal processing (DSP). This paper presents the use of an FPGA in the implementation of a DSP trainer that will serve as an educational tool to effectively teach the fundamental principles of digital signal processing. This trainer is capable of performing a 1024-point discrete Fourier transform, convolution, correlation, and finite impulse response filter, which includes a low pass, high pass, and band pass filter. This paper also describes the capability of an FPGA to internally generate different input signals like a square wave, triangle wave, and a sine wave, to accept an external signal from a microphone, an MP3 player and the like, to output the transformed signal in digital or analog form, and through the use of a VGA port, to visualize the signals in a display device making this trainer low cost.

Post-disaster rescue facility: Human detection and geolocation using aerial drones

The research focuses on the implementation of a human detection and geolocation system using aerial drones to complement search and rescue. The study includes the characterization of the human detection system for thermal and optical imagery by determining the frame accuracy, true and false positive rates. Geolocation was achieved using triangulated-adjusted GPS data and integration of Google Maps.

Brain-computer interface and voice-controlled 3D printed prosthetic hand

Current designs for 3D printed hand prosthetics are only capable of basic hand gestures given their fully mechanical structure. That said, the purpose of this thesis is to give users greater flexibility and control over 3D printed hand prosthetics by modifying and improving existing open-source prosthetics models. This will be accomplished by integrating two control modules with the 3D printed prosthetic hand - (a) a brain-computer interface, and (b) a voice recognition module - which will serve as its two primary modes of control.

Towards building a predictive model for remote river quality monitoring for mining sites

Most, if not all, mining sites in the Philippines are not equipped with expensive or modern monitoring tools to check for quality of soil, water and air elements which are relevant to ensure safety and wellness of miners. This study focused on the development of low cost mobile electronic sensors to monitor quality of water from rivers near mining sites. Low cost electronic sensors connected to a smart phone were developed to capture dissolved oxygen (DO2), pH, Turbidity, Temperature, and Salinity. The data for mercury (Hg) and arsenic (As) were obtained through AAS analyses to form baseline data for the model. Data was collected for over a period of one year, with site visits once every two months. A conditional inference tree (ctree) using recursive binary partitioning was used to generate the prediction model using 70 - 30 split on the training and test data set. The multi-feature model returns Good, Not Good or Unknown based on the scores of each element. The results showed a possible three feature model with significant results for site, salinity and pH balance.

Design and Development of a Wireless Sensor Network Framework for Water Quality Remote Monitoring

This study involves the design and development of a wireless sensor network (WSN) that integrates several sensing modules into a fully-functional system. The overall system is composed of a remote server, a controller node, and several sensing modules. The controller node is implemented using an Android mobile phone with Bluetooth and 3G capabilities. Bluetooth is used to communicate with the various sensing modules; while 3G is used to relay data to the remote server. The sensing modules utilize an Arduino Mega 2560 (with the sensor circuits) and a Bluetooth shield. Test results show that this framework is a viable design for WSN systems and can be used for remote installations that can be continuously upgraded over time.

Design of autonomous sensor nodes for remote soil monitoring in tropical banana plantation

Determining the effect of Fusarium oxysporum f. sp. cubense Tropical Race 4 on various soil parameters is essential in modeling and predicting its occurrence in banana plantations. One way to fulfill this is through a sensor network that will continuously and automatically monitor environmental conditions at suspect locations for an extended period of time. A wireless sensor network was developed specifically for this purpose. This sensor network is capable of measuring soil acidity, moisture, temperature, and conductivity. The designed prototype made use of off-the-shelf Parrot Flower Power soil sensor, pH sensor, Bluno Beetle, battery, and 3D-printed materials, catering specifically to the conditions of tropical banana plantations with consideration for sensor node size, communication, and power. Sensor nodes were tested on both simulated tropical environments and on an actual banana plantation in San Jose, General Santos City, Philippines. Challenges were resolved through iterative design and development of prototypes. Several tests including temperature and weather resilience, and structural stress tests were done to validate the design. Findings showed that the WSN nodes developed for this purpose are resilient to high tropical temperatures for up to 12 hours of continuous exposure, are able to withstand compressive forces of up to 8880.6 N, and can reliably collect data automatically from the area 47.96% of the time at an hourly frequency under actual field conditions.