Toward the design of persuasive systems for a healthy workplace: a real-time posture detection.

Persuasive technologies, in connection with human factor engineering requirements for healthy workplaces, have played a significant role in ensuring a change in human behavior. Healthy workplaces suggest different best practices applicable to body posture, proximity to the computer system, movement, lighting conditions, computer system layout, and other significant psychological and cognitive aspects. Most importantly, body posture suggests how users should sit or stand in workplaces in line with best and healthy practices. In this study, we developed two study phases (pilot and main) using two deep learning models: convolutional neural networks (CNN) and Yolo-V3. To train the two models, we collected posture datasets from creative common license YouTube videos and Kaggle. We classified the dataset into comfortable and uncomfortable postures. Results show that our YOLO-V3 model outperformed CNN model with a mean average precision of 92%. Based on this finding, we recommend that YOLO-V3 model be integrated in the design of persuasive technologies for a healthy workplace. Additionally, we provide future implications for integrating proximity detection taking into consideration the ideal number of centimeters users should maintain in a healthy workplace.

African foods for deep learning-based food recognition systems dataset.

African foods have socio-cultural significance that extends through migration, tourism, and marriage. Africans travel and integrate within the continent through intermarriages. There are over a thousand cultural aspects that differ such as language, food, dressing, beliefs and customs. Food is one of the cultural aspects that Africans embrace quickly as they migrate and integrate socio-culturally. We considered the limited representation of African food research in the HCI community and propose to contribute the rich significant food datasets from two African countries: Cameroon and Ghana. List of Cameroonian foods collected are: Ekwang, Eru and Ndole. In addition, the list of Ghanaian foods we collected are: Jollof Rice, Palm-nut Soup and Waakye. Given the cultural diversity and our study's goal for cultural inclusion, we interacted with at least two locals from the selected countries, and they confirmed that these foods were universally recognized within their respective countries. The datasets were collected from YouTube, Facebook, the field (restaurants), Creative Common Attribution Google Images, and other Creative Commons Attribution sources. A total of 204 images of Ekwang, 206 images of Eru and 205 images of Ndole were collected. In addition, we collected a total of 347 images of Jollof Rice, 392 images of Palm-nut Soup and 400 images of Waakye. We present a meta-data description of the data, quality assessments of our dataset and opportunities for the HCI community to explore in the future.