Joseph Korpela

Osaka University | Handai · Graduate School of Information Science and Technology

Owing to the recent proliferation of smartphones and the SNS, a large number of images taken by smartphones at various places have been uploaded to SNSs. In addition, smartphones are equipped with various sensors such as Wi-Fi modules that enable us to generate an image associated with the sensory information that represents the context in which th...

Background Recent advances in sensing technologies have enabled us to attach small loggers to animals in their natural habitat. It allows measurement of the animals’ behavior, along with associated environmental and physiological data and to unravel the adaptive significance of the behavior. However, because animal-borne loggers can now record mult...

Omnivorous gulls (Laridae) are known to feed on insects. Few studies have reported, however, how, when, and where they do so. In this study, we attached a GPS-video logger to Black-tailed Gulls Larus crassirostris during the breeding season. Video recordings were obtained of gulls capturing flying insects over land and sea. Some insects were identi...

Unravelling the secrets of wild animals is one of the biggest challenges in ecology, with bio-logging (i.e., the use of animal-borne loggers or bio-loggers) playing a pivotal role in tackling this challenge. Bio-logging allows us to observe many aspects of animals’ lives, including their behaviours, physiology, social interactions, and external env...

This paper presents a robust unsupervised method for recognizing factory work using sensor data from body-worn acceleration sensors. In line-production systems, each factory worker repetitively performs a predefined work process with each process consisting of a sequence of operations. Because of the difficulty in collecting labeled sensor data fro...

This paper presents an unsupervised method for recognizing assembly work done by factory workers by using wearable sensor data. Such assembly work is a common part of line production systems and typically involves the factory workers performing a repetitive work process made up of a sequence of manual operations, such as setting a board on a workbe...

Animal-borne data loggers, i.e., biologgers, allow researchers to record a variety of sensor data from animals in their natural environments. This data allows biologists to observe many aspects of the animals' lives, including their behavior, physiology, social interactions, and external environment. However, the need to limit the size of these dev...

This paper presents a low-cost privacy preserving method for recognizing object-based activities through the use of near-infrared (NIR) reflective markers. The NIR markers are thin pieces of durable reflective material that can be attached to objects, with their movement captured using a webcam that has been modified to capture NIR images. The came...

Although sleep is essential to healthy living, many people have issues related to insufficient or poor quality sleep. In this study, we propose a method for unobtrusively detecting body movements during sleep by measuring changes in Wi-Fi signal strength between two Wi-Fi-enabled devices because prior research has found a correlation between sleep...

We present a fingerprinting-based Wi-Fi indoor positioning method robust against temporal fluctuations and spatial instability in Wi-Fi signals. An ensemble is created using randomized weak position estimators, with the estimators specialized to different areas in the target environment and designed so that each area has estimators that rely on dif...

This paper presents a method for evaluating toothbrushing performance using audio data collected by a smartphone. This method first conducts activity recognition on the audio data to classify segments of the data into several classes based on the brushing location and type of brush stroke. These recognition results are then used to compute several...

This paper presents an energy-aware method for recognizing time series acceleration data containing both activities and gestures using a wearable device coupled with a smartphone. In our method, we use a small wearable device to collect accelerometer data from a user's wrist, recognizing each data segment using a minimal feature set chosen automati...

This paper presents a new method for evaluating tooth brushing performance using audio collected from a smartphone. To do this, we use hidden Markov models (HMMs) to recognize audio data that include various types of tooth brushing actions, such as brushing the outer surface of the front teeth and brushing the inner surface of the back teeth. We th...

This paper proposes a new method that can recognize both activities and gestures by using acceleration data. While both activity recognition techniques and gesture recognition techniques employ acceleration data, these techniques are studied independently due to the large difference between the characteristics of activity sensor data and gesture se...

Transdisciplinary research is a rapidly expanding part of science and engineering, demanding new methods for connecting results across fields. In biomedicine for example, modeling complex biological systems requires linking knowledge across multiple levels of science, from genes to disease. The move to multilevel research requires new strategies; i...