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Sökning: swepub > Konferensbidrag > Göteborgs universitet

  • Resultat 21-30 av 22125
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21.
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22.
  • Karlsson, Katarina A. (författare)
  • The Essentially Feminine—an investigation through artistic practice in Early Modern music
  • 2013
  • Ingår i: Symposium on Critical Heritage : Excavate Repressions.
  • Konferensbidrag (refereegranskat)abstract
    • The territoriality of 'masculine' and 'feminine' is an ongoing process, where boarders are constantly stretched and moved. To even use the word 'feminine' is a challenge and in combination with the word 'essential' it is yet more provoking. However, the notion of feminity is interesting, since it is used by the PR-industry as something absolute and desirable for women. This project wants to unviel the cultural heritage of the notion of femininity in the past, to learn something about power structures today. “The woman is putrefaction with a pretty face”1 From the Malleas Maleficarum (1487), that book on witchcraft that served as instruction manual for the Spanish inquisition, to the way in which women are presented in much of twentieth century American rap music, the archetype of the ”wicked woman” permeates western cultural history. Musical discourse has never been immune to the use of gendered terminology. Mysogyny is part of our cultural heritage.
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23.
  • Matić, Teodora, et al. (författare)
  • Unsupervised Learning from Motion Sensor Data to Assess the Condition of Patients with Parkinson’s Disease
  • 2019
  • Ingår i: AIME 2019. - Cham : Springer. - 9783030216429 - 9783030216412 ; , s. 420-424
  • Konferensbidrag (refereegranskat)abstract
    • Parkinson’s disease (PD) is a chronic neurodegenerative disorder that predominantly affects the patient’s motor system, resulting in muscle rigidity, bradykinesia, tremor, and postural instability. As the disease slowly progresses, the symptoms worsen, and regular monitoring is required to adjust the treatment accordingly. The objective evaluation of the patient’s condition is sometimes rather difficult and automated systems based on various sensors could be helpful to the physicians. The data in this paper come from a clinical study of 19 advanced PD patients with motor fluctuations. The measurements used come from the motion sensors the patients wore during the study. The paper presents an unsupervised learning approach applied on this data with the aim of checking whether sensor data alone can indicate the patient’s motor state. The rationale for the unsupervised approach is that there was significant inter-physician disagreement on the patient’s condition (target value for supervised machine learning). The input to clustering came from sensor data alone. The resulting clusters were matched against the physicians’ estimates showing relatively good agreement.
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24.
  • Nilsson, Magnus (författare)
  • Ageing Single Men in Rural Areas
  • 2011
  • Ingår i: paperpresentation på The 10th Conference of the European Sociological Association, Social relations in turbulent times, University of Geneva, Schweiz, 7-10 September 2011..
  • Konferensbidrag (refereegranskat)
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25.
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26.
  • Nilsson, Magnus (författare)
  • The Discourse of Ageism within Anti-ageist Policy
  • 2008
  • Ingår i: Paper presenterat vid The 6th International Symposium on Cultural Gerontology. Extending Time, Emerging Realities, Imagining Response. University of Lleida, Spanien, 16-18 oktober 2008.
  • Konferensbidrag (refereegranskat)
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27.
  • Nilsson, Magnus (författare)
  • Who and what counts as old?
  • 2007
  • Ingår i: Paper presenterat vid INTER-European Cultural Studies Conference, ACSIS, Linköpings Universitet, Norrköping 11-13 juni 2007..
  • Konferensbidrag (refereegranskat)
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28.
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29.
  • Thomas, Ilias, et al. (författare)
  • Using measurements from wearable sensors for automatic scoring of Parkinson's disease motor states : Results from 7 patients
  • 2017
  • Ingår i: 2017 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC). - New York : IEEE. - 1094-687X. - 9781509028092 - 9781509028108 ; , s. 131-134
  • Konferensbidrag (refereegranskat)abstract
    • The objective of this study was to investigate the validity of an objective gait measure for assessment of different motor states of advanced Parkinson's disease (PD) patients. Seven PD patients performed a gait task up to 15 times while wearing sensors on their upper and lower limbs. Each task was performed at specific points during a test day, following a single dose of levodopa-carbidopa. At the time of the tasks the patients were video recorded and three movement disorder experts rated their motor function on three clinical scales: a treatment response scale (TRS) that ranged from −3 (very bradykinetic) to 0 (ON) to +3 (very dyskinetic), a dyskinesia score that ranged from 0 (no dyskinesia) to 4 (extreme dyskinesia), and a bradykinesia score that ranged from 0 (no bradykinesia) to 4 (extreme bradykinesia). Raw accelerometer and gyroscope data of the sensors were processed and analyzed with time series analysis methods to extract features. The utilized features quantified separate limb movements as well as movement symmetries between the limbs. The features were processed with principal component analysis and the components were used as predictors for separate support vector machine (SVM) models for each of the three scales. The performance of each model was evaluated in a leave-one-patient out setting where the observations of a single patient were used as the testing set and the observations of the other 6 patients as the training set. Root mean square error (RMSE) and correlation coefficients for the predictions showed a good ability of the models to map the sensor data into the rating scales. There were strong correlations between the SVM models and the mean ratings of TRS (0.79; RMSE=0.70), bradykinesia score (0.79; RMSE=0.47), and bradykinesia score (0.78; RMSE=0.46). The results presented in this paper indicate that the use of wearable sensors when performing gait tasks can generate measurements that have a good correlation to subjective expert assessments.
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