Multi-sensor context aware clothing
K. Van Laerhoven,Albrecht Schmidt,Hans Gellersen +2 more
- 01 Oct 2002
- pp 49-56
TL;DR: Experiments with a body-distributed sensor system investigate the influence of two factors that affect classification of what has been sensed: an increase in sensors enhances recognition, while adding new classes or contexts depreciates the results.
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Abstract: Inspired by perception in biological systems, distribution of a massive amount of simple sensing devices is gaining more support in detection applications. A focus on fusion of sensor signals instead of strong analysis algorithms, and a scheme to distribute sensors, results in new issues. Especially in wearable computing, where sensor data continuously changes, and clothing provides an ideal supporting structure for simple sensors, this approach may prove to be favourable. Experiments with a body-distributed sensor system investigate the influence of two factors that affect classification of what has been sensed: an increase in sensors enhances recognition, while adding new classes or contexts depreciates the results. Finally, a wearable computing related scenario is discussed that exploits the presence of many sensors.
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Figures
Figure 8. Dispersion of sensor data for two contexts, black and white, and how it relates to performance of a context awareness algorithm: (1) a large dispersion indicates that algorithms can easily distinguish the two contexts, while (2) a small dispersion suggests the opposite. The data is visualized by circles, while the means of both data sets are designated by crosses. 
Figure 10. The 3D dispersion plot with the variance of the datasets incorporated. 
Figure 9. The 3D evaluation plot with the dispersion of means as unit for the Z axis. The X and Y axes represent the numbers of sensors and the number of contexts respectively. 
Table 1. Part of the microcontroller’ s source code that converts the pulses on pin C0 into an acceleration value. 
Figure 1. Centralized processing and fusion of the data. 
Figure 2. The PIC-based sensor-reading module, able to read thirty sensor values at once and stream them to the RS232 serial port. Right are a few of the accelerometers.
Citations
Activity recognition from user-annotated acceleration data
Ling Bao,Stephen S. Intille +1 more
- 21 Apr 2004
TL;DR: This is the first work to investigate performance of recognition algorithms with multiple, wire-free accelerometers on 20 activities using datasets annotated by the subjects themselves, and suggests that multiple accelerometers aid in recognition.
A tutorial on human activity recognition using body-worn inertial sensors
TL;DR: In this paper, the authors provide a comprehensive hands-on introduction for newcomers to the field of human activity recognition using on-body inertial sensors and describe the concept of an Activity Recognition Chain (ARC) as a general-purpose framework for designing and evaluating activity recognition systems.
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Quantifying human exposure to air pollution - moving from static monitoring to spatio-temporally resolved personal exposure assessment
TL;DR: A novel conceptual model for the integrated assessment of human exposure to air pollutants taking into account latest technological capabilities and contextual information is proposed.
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Intelligent Assistive Technology Applications to Dementia Care: Current Capabilities, Limitations, and Future Challenges
Ashok Bharucha,Vivek Anand,Jodi Forlizzi,Mary Amanda Dew,Charles F. Reynolds,Scott Stevens,Howard D. Wactlar +6 more
TL;DR: The authors conducted an extensive search of the computer science, engineering, and medical databases to review intelligent cognitive devices, physiologic and environmental sensors, and advanced integrated sensor networks that may find future applications in dementia care.
Electroactive polymer-based devices for e-textiles in biomedicine
Federico Carpi,Danilo De Rossi +1 more
- 01 Sep 2005
TL;DR: The most highly performing EAP-based devices developed by the lab and other research groups for sensing, actuation, electronics, and energy generation/storage are presented, with reference to their already demonstrated or potential applicability to electronic textiles.
366
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