This paper proposes the concept of Well-being computing which is an information technology for improving not only our health as physical aspect but also our happiness as psy-chological aspect, and shows its potential from the sleep perspective. Concretely, this paper introduces “our personal-ized sleep monitoring system” as the well-being computing technologies and shows the following implications as its ef-fectiveness: (1) from the viewpoint of the service based on the real-time sleep, (1-a) good health is provided through a stable sleep of aged person in care house by reducing their sleep disturbance which may be occurred in diaper exchange, while happiness is provided by the smooth diaper exchange when aged person have a deep/light sleep; (1-b) good health is provided through a sufficient sleep time acquired by a fast falling asleep, while happiness is provided by releasing from anxiety of the insufficient sleep such as insomnia; and (2) from the viewpoint of the service based on the long-term sleep, (2-a) good health is provided through a deep sleep by continuing the daytime activities (such as a walking) which contribute to deriving a deep sleep, while happiness is provided by achieving a deep sleep through a change of life style; (2-b) good health is provided through a good sleep by keeping good bed condition (e.g., a change of a pillow or mattress when cotton/spring is deteriorated), while happiness is provided through a discovery of suitable bedding (such as suitable pillow or bed).

Interprofessional Collaboration in dementia care is an important theme. But there are few Support systems that make it possible to share and raise awareness of the situation of the person with dementia. Therefore, using a dementia inspection method named Action Observation Sheet (AOS), we devel-oped an Interprofessional Collaborative System to raise awareness. We have conducted practical experiments to confirm if the system is effective for family and staff. The results show the system to be effective to increase awareness. The family and staff could use the results provided by the system to support people with dementia with more understanding.

In this position paper we introduce our approach to positive computing by developing and integrating methods for future assistant and companion agents which could help us a) avoid making mistakes due to biases caused by insufficient knowledge, b) be more empathic and righteous, c) be more sensitive and thoughtful. We present text processing techniques for automatic discovery of possible reasoning errors and provide hints to make users doubt their beliefs when there is a possibility of harm. We present existing sources and methods, discuss on how natural language processing technologies could contribute to various aspects of well-being by giving examples of systems we develop, and describe the strengths and weaknesses of our approach.

This paper reports a cradle sound system creating and reproducing sounds and music appropriate for human sleep with heartbeat and respiration signals sensed by biological sensors. To get further supporting evidence, we started a study aiming at exploring what sound attributes, such as waveforms, tones, and tempos, are necessary for a sound capable of improving sleep latency. We expected that a cradle sound whose tempo was slightly slower than those of heartbeat and respiration could slow them and could promote natural sleep. Subjects listening to this sound during their sleep showed: (1) Multiple sound types with different tones have an effect to shorten sleep latency. (2) Remarkable effects are observed in subjects with long sleep latency. (3) Sustained synthetic chord used for inducing respiration did not improve sleep latency. (4) There is no correlation between subject’s sensibility evaluation to sound and the effect shortening sleep latency.

As countermeasure for preventing dementia of aging population, coimagination method has been developed. The coimagination method helps participants in utilizing brain cognitive functions of maintaining recent episodic memorization, retention and recall by the process of conversations. Hence, the risk of older adults in getting into mild cognitive impairment (MCI), which is a previous stage of dementia caused by disuse of brain cognitive functions, will decline. However, we observed situations of some older adults that recent episodic memory functions were not activated as expected. Such situations are older adults who talk about knowledge rather than episodic memories or older adults who talk about past experiences rather than recent experiences. Therefore, a novel coimagination program named coimagination method with expedition was developed to solve these situations. By adding expedition in a sightseeing area before the coimagination method, older adults have the opportunity to find topic of conversations through expedition. During conversation supported by the coimagination method, older adults are expected to recall their episodic memories in expedition and talk about it. The purpose of this research is to verify the effect of the coimagination method with expedition in older adults, by comparing mental time of older adults in the coimagination methods with and without expedition. Firstly, we estimate the mental time of older adults by analyzing their utterances during conversations supported by both coimagination methods. The past, present and future mental times of participants are enumerated in percentage. Secondly, we study the mental time travelling of participants during conversations. Finally, we study the transition points of mental time to find tendency of participants to talk about recent experiences. In this research, the analytical results validate the effectiveness of helping older adults to talk about recent episodic memories during conversation supported by the coimagination method with expedition compared to the coimagination method.

In the field of self-help groups for recovering from developmental disorders or alcohol dependence or the other problem, a meeting of non-crosstalk style has been used. On the meeting style, participants speak about one topic without conversation with the other participants, and advising and asking to others are not recommended besides. We are proposing an online meeting system that is specialized to support non-crosstalk style meeting. Now, we would like to develop an online agent who can perform like a human participant or more useful for participants. Since the developments of above online meeting system and autonomous agents contribute to supporting many people in the self-help field, this study has an impact in the designing methods for making better well-being space environment. In order to inspire human behaviors to the agent, this paper shows analysis the results of online humans meetings using our proposed system. As the experimental results which were compared with a classical style system, it has revealed about proposed system as follows: (1) frustrating with rules of non-crosstalk is small, (2) conversational speech didn’t reduce, (3) conversational speeches were increasing along with the time but they are leading to prevent from decreasing the number of speeches, and (4) more sensitive to the speed of displaying speeches.

This paper proposes a novel method to estimate sleep stage in real-time with a non-contact device. The proposed method employs the trigonometric function regression model to estimate prospective heart rate from the partially obtained heart rate and calculates the sleep stage from the estimated heart rate. This paper conducts the subject experiment and it is revealed that the proposed method enables to estimate the sleep stage in real-time, in particular the proposed method has the equivalent estimation accuracy as the previous method that estimates the sleep stage according to the entire heart rate during sleeping.

Highly sensitive low noise electrodes, capability of fast processing of multivariate signals, low cost of hardware and wireless communication have widen the possibilities of the use of electroencephalogram (EEG) data for various applications. These applications are not only restricted to medical investigations (like epileptic seizures, monitoring anesthesia or brain functions etc.), but also for well-being of disabled patients, as well as for entertainments like playing games. Our focus in this study is BCI applications based on identification of Event Related Potential (ERP) P300. One such application is BCI speller, which is used in our experiments. BCI speller on the market use 8 probes and take 72 seconds to collect data to reliably spell a single character. The motivation of this work is to reduce the number of probes and the time needed to spell a letter. A commercial product should reliably work for every user (customer). Such a large number of probes and long time to spell a letter are necessary to ensure correct recognition. We have shown that if we identify the position of the probes appropriately for an individual, as few as two probes could give even better results. All experiments are conducted at our in-house facility, where most ot the subjects undergone no prior training.

Due to the advances in medical science, increasing health consciousness, improved quality of food, the average human life span has increased to a great extent. On the other hand, stresses of modern life, overwork and less sleep, increased usage of digital devices and internet, less exercise, are leading us to poor quality of life. Elderly people are more vulnerable to reduced life quality due to deterioration of both physical and mental health. People at any age need to maintain a minimum level of wellbeing to pursue his or her daily activities to lead a fulfilling life. Thus the need of assessing and restoring wellness is very important. Fortunately the progress of information and communication technologies provide use sensor devices and computing platform to feel, monitor and restore the wellness. In this work, a study has been done to define and determine wellness related to daily activities data obtained from various sensors and provide recommendation to the user regarding improvement of life style to achieve wellness. A small-scale experiment has been done using a simple lifelog device. The daily activities data including walking steps, sleep time, inactive period, calories burned are collected from 8 subjects. In addition food intake, eating times, cell phone usage, messaging time, time of interaction with other people and solo time are also manually collected. The correlation of physical activities (walking time, exercise time), mental activities (cell phone usage, study time, interaction with friends) and sleep patterns are studied. A simple parameter Tiredness Factor has been proposed to determine wellness and a recommendation system for improving wellness has been developed. Questionnaire from the subjects about the personal feelings of wellness has been noted and used to evaluate our proposal.

Texts posted on the web by users from diverse cultures provide a nearly endless source of data that researchers can use to study human thoughts and language patterns. However, unless care is taken to avoid it, models may be developed in one cultural setting and deployed in another, leading to unforeseen consequences. We explore the effects of using models built from a corpus of texts from multiple cultures in order to learn about each represented people group separately. To do this, we employ a topic modeling approach to quantify open-ended writing responses describing personal values and everyday behaviors in two distinct cultures. We show that some topics are more prominent in one culture compared to the other, while other topics are mentioned to similar degrees. Furthermore, our results indicate that culture influences how value-behavior relationships are exhibited. While some relationships exist in both cultural groups, in most cases we see that the observed relations are dependent on the cultural background of the data set under examination.