Quantification and mitigation of the instrument effects and uncertainties of the airborne limb imaging FTIR GLORIA

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an infrared imaging FTS (Fourier transform spectrometer) with a 2-D infrared detector that is operated on two high-flying research aircraft. It has flown on eight campaigns and measured along more than 300 000 km of flight track.This paper details our instrument calibration and characterization efforts, which, in particular, almost exclusively leverage in-flight data. First, we present the framework of our new calibration scheme, which uses information from all three available calibration sources (two blackbodies and upward-pointing “deep space” measurements). Part of this scheme is a new algorithm for correcting the erratically changing nonlinearity of a subset of detector pixels and the identification of the remaining bad pixels.Using this new calibration, we derive a 1σ bound of 1 % on the instrument gain error and a bound of 30 nW cm−2 sr−1 cm on the instrument offset error. We show how we can examine the noise and spectral accuracy for all measured atmospheric spectra and derive a spectral accuracy of 5 ppm on average. All these errors are compliant with the initial instrument requirements.We also discuss, for the first time, the pointing system of the GLORIA instrument. Combining laboratory calibration efforts with the measurement of astronomical bodies during the flight, we can achieve a pointing accuracy of 0.032∘, which corresponds to one detector pixel.The paper concludes with a brief study of how these newly characterized instrument parameters affect temperature and ozone retrievals. We find that the pointing uncertainty and, to a lesser extent, the instrument gain uncertainty are the main contributors to the error in the result

Data-driven analysis of interactions between people with dementia and a tablet device

Abstract In the project I-CARE a technical system for tablet devices is developed that captures the personal needs and skills of people with dementia. The system provides activation content such as music videos, biographical photographs and quizzes on various topics of interest to people with dementia, their families and professional caregivers. To adapt the system, the activation content is adjusted to the daily condition of individual users. For this purpose, emotions are automatically detected through facial expressions, motion, and voice. The daily interactions of the users with the tablet devices are documented in log files which can be merged into an event list. In this paper, we propose an advanced format for event lists and a data analysis strategy. A transformation scheme is developed in order to obtain datasets with features and time series for popular methods of data mining. The proposed methods are applied to analysing the interactions of people with dementia with the I-CARE tablet device. We show how the new format of event lists and the innovative transformation scheme can be used to compress the stored data, to identify groups of users, and to model changes of user behaviour. As the I-CARE user studies are still ongoing, simulated benchmark log files are applied to illustrate the data mining strategy. We discuss possible solutions to challenges that appear in the context of I-CARE and that are relevant to a broad range of applications.</jats:p

Security and user acceptance of an intelligent home emergency call system for older people living at home with limited daily living skills and receiving home care

Background Technically based support measures are becoming increasingly more important in an aging society. Such support measures can provide a self-determined life in familiar surroundings despite the need for care. An example for such a support measure is an intelligent home emergency call system (iHNR system), which automatically detects critical situations (e.g. falling down), transmits this information to an emergency call center and therefore initiates assistance faster. Objective The aim of this uncontrolled, two center observational study was to evaluate the security and acceptance of an iHNR system used by older people receiving home care. Material and methods The study was carried out based on 51 subjects with at least a 6-month observation period using the iHNR system. The iHNR system was installed in all homes of the participants. Interviews about acceptance, perceived and objective security, impact on independence and usability of the new iHNR system were conducted. Analysis was performed with particular respect to depression, quality of life, frailty and self-estimated need for assistance. Results A total of 39 complete records were collected and evaluated. The participants represented a vulnerable group of people with rather depressive moods, negative quality of life and a high level of frailty without significant changes over the observation period. Positive results were found regarding subjective and objective security and acceptance as well as ease of operation of the iHNR system. The fear of falling was only marginally influenced. Conclusion Acceptance regarding the new iHNR system was high. The system provoked a stronger sense of security while at the same time leading to a reduced sense of control. The system seems to be able to detect critical events and can automatically and quickly alert the necessary help services. Therefore, people in need of care can remain longer in their own homes

Quantification and mitigation of the instrument effects and uncertainties of the airborne limb imaging FTIR GLORIA

The Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) is an infrared imaging FTS (Fourier transform spectrometer) with a 2-D infrared detector that is operated on two high-flying research aircraft. It has flown on eight campaigns and measured along more than 300 000 km of flight track.This paper details our instrument calibration and characterization efforts, which, in particular, almost exclusively leverage in-flight data. First, we present the framework of our new calibration scheme, which uses information from all three available calibration sources (two blackbodies and upward-pointing “deep space” measurements). Part of this scheme is a new algorithm for correcting the erratically changing nonlinearity of a subset of detector pixels and the identification of the remaining bad pixels.Using this new calibration, we derive a 1σ bound of 1 % on the instrument gain error and a bound of 30 nW cm−2 sr−1 cm on the instrument offset error. We show how we can examine the noise and spectral accuracy for all measured atmospheric spectra and derive a spectral accuracy of 5 ppm on average. All these errors are compliant with the initial instrument requirements.We also discuss, for the first time, the pointing system of the GLORIA instrument. Combining laboratory calibration efforts with the measurement of astronomical bodies during the flight, we can achieve a pointing accuracy of 0.032∘, which corresponds to one detector pixel.The paper concludes with a brief study of how these newly characterized instrument parameters affect temperature and ozone retrievals. We find that the pointing uncertainty and, to a lesser extent, the instrument gain uncertainty are the main contributors to the error in the result

Data-driven analysis of interactions between people with dementia and a tablet device

In the project I-CARE a technical system for tablet devices is developed that captures the personal needs and skills of people with dementia. The system provides activation content such as music videos, biographical photographs and quizzes on various topics of interest to people with dementia, their families and professional caregivers. To adapt the system, the activation content is adjusted to the daily condition of individual users. For this purpose, emotions are automatically detected through facial expressions, motion, and voice. The daily interactions of the users with the tablet devices are documented in log files which can be merged into an event list. In this paper, we propose an advanced format for event lists and a data analysis strategy. A transformation scheme is developed in order to obtain datasets with features and time series for popular methods of data mining. The proposed methods are applied to analysing the interactions of people with dementia with the I-CARE tablet device. We show how the new format of event lists and the innovative transformation scheme can be used to compress the stored data, to identify groups of users, and to model changes of user behaviour. As the I-CARE user studies are still ongoing, simulated benchmark log files are applied to illustrate the data mining strategy. We discuss possible solutions to challenges that appear in the context of I-CARE and that are relevant to a broad range of applications