IntelliChair: a non-intrusive sitting posture and sitting activity recognition system

Current Ambient Intelligence and Intelligent Environment research focuses on the interpretation of a subject’s behaviour at the activity level by logging the Activity of Daily Living (ADL) such as eating, cooking, etc. In general, the sensors employed (e.g. PIR sensors, contact sensors) provide low resolution information. Meanwhile, the expansion of ubiquitous computing allows researchers to gather additional information from different types of sensor which is possible to improve activity analysis. Based on the previous research about sitting posture detection, this research attempts to further analyses human sitting activity. The aim of this research is to use non-intrusive low cost pressure sensor embedded chair system to recognize a subject’s activity by using their detected postures. There are three steps for this research, the first step is to find a hardware solution for low cost sitting posture detection, second step is to find a suitable strategy of sitting posture detection and the last step is to correlate the time-ordered sitting posture sequences with sitting activity. The author initiated a prototype type of sensing system called IntelliChair for sitting posture detection. Two experiments are proceeded in order to determine the hardware architecture of IntelliChair system. The prototype looks at the sensor selection and integration of various sensor and indicates the best for a low cost, non-intrusive system. Subsequently, this research implements signal process theory to explore the frequency feature of sitting posture, for the purpose of determining a suitable sampling rate for IntelliChair system. For second and third step, ten subjects are recruited for the sitting posture data and sitting activity data collection. The former dataset is collected byasking subjects to perform certain pre-defined sitting postures on IntelliChair and it is used for posture recognition experiment. The latter dataset is collected by asking the subjects to perform their normal sitting activity routine on IntelliChair for four hours, and the dataset is used for activity modelling and recognition experiment. For the posture recognition experiment, two Support Vector Machine (SVM) based classifiers are trained (one for spine postures and the other one for leg postures), and their performance evaluated. Hidden Markov Model is utilized for sitting activity modelling and recognition in order to establish the selected sitting activities from sitting posture sequences.2. After experimenting with possible sensors, Force Sensing Resistor (FSR) is selected as the pressure sensing unit for IntelliChair. Eight FSRs are mounted on the seat and back of a chair to gather haptic (i.e., touch-based) posture information. Furthermore, the research explores the possibility of using alternative non-intrusive sensing technology (i.e. vision based Kinect Sensor from Microsoft) and find out the Kinect sensor is not reliable for sitting posture detection due to the joint drifting problem. A suitable sampling rate for IntelliChair is determined according to the experiment result which is 6 Hz. The posture classification performance shows that the SVM based classifier is robust to “familiar” subject data (accuracy is 99.8% with spine postures and 99.9% with leg postures). When dealing with “unfamiliar” subject data, the accuracy is 80.7% for spine posture classification and 42.3% for leg posture classification. The result of activity recognition achieves 41.27% accuracy among four selected activities (i.e. relax, play game, working with PC and watching video). The result of this thesis shows that different individual body characteristics and sitting habits influence both sitting posture and sitting activity recognition. In this case, it suggests that IntelliChair is suitable for individual usage but a training stage is required.

Conceptualising cosmopolitanism and entrepreneurship through the lens of the three-dimensional theory of power

Purpose – The paper aims to conceptualise cosmopolitanism drivers from the third-level power perspective by drawing on Lukes’ (1974; 2005) theory of power. In addition, the paper aims to investigate the relationship between entrepreneurs’ cosmopolitan dispositions and habitus, i.e. a pattern of an individual’s demeanour, as understood by Bourdieu. Design/methodology/approach – This conceptual paper makes use of Bourdieu’s framework (habitus) by extending it to the urban cosmopolitan environment and linking habitus to the three-dimensional theory of power and, importantly, to the power’s third dimension – preference-shaping. Findings – Once cosmopolitanism is embedded in the urban area’s values, this creates multiple endless rounds of mutual influence (by power holders onto entrepreneurs via political and business elites, and by entrepreneurs onto power holders via the same channels), with mutual benefit. Therefore, mutually beneficial influence that transpires in continuous support of a cosmopolitan city’s environment may be viewed as one of the factors that enhances cosmopolitan cities’ resilience to changes in macroeconomic conditions. Originality/value – The paper offers a theoretical model that enriches the understanding of the power-cosmopolitanism-entrepreneurship link, by emphasising the preference-shaping capacity of power, which leads to the embedment of cosmopolitanism in societal values. As a value shared by political and business elites, cosmopolitanism is also actively promoted by entrepreneurs through their disposition and habitus. This ensures not only their willing compliance with power and the environment, but also their enhancement of favourable business conditions. Entrepreneurs depart from mere acquiescence (to power and its explicit dominance), and instead practice their cosmopolitan influence by active preference-shaping.