A Bayesian Assessment of Real-World Behavior During Multitasking
Multitasking is common in everyday life, but its effect on activities of daily living is not well understood. Critical appraisal of performance for both healthy individuals and patients is required. Motor activities during meal preparation were monitored in healthy individuals with a wearable sensor...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Springer-Verlag
2017
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| Online Access: | http://hdl.handle.net/1721.1/110944 https://orcid.org/0000-0002-8503-3973 |
| _version_ | 1811074516361674752 |
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| author | Fei, Joan Green, David A Hussain, Amir Howard, Newton Bergmann, Jeroen H. M. |
| author2 | Massachusetts Institute of Technology. Media Laboratory |
| author_facet | Massachusetts Institute of Technology. Media Laboratory Fei, Joan Green, David A Hussain, Amir Howard, Newton Bergmann, Jeroen H. M. |
| author_sort | Fei, Joan |
| collection | MIT |
| description | Multitasking is common in everyday life, but its effect on activities of daily living is not well understood. Critical appraisal of performance for both healthy individuals and patients is required. Motor activities during meal preparation were monitored in healthy individuals with a wearable sensor network during single and multitask conditions. Motor performance was quantified by the median frequencies (fm) of hand trajectories and wrist accelerations. The probability that multitasking occurred based on the obtained motor information was estimated using a Naïve Bayes Model, with a specific focus on the single and triple loading conditions. The Bayesian probability estimator showed task distinction for the wrist accelerometer data at the high and low value ranges. The likelihood of encountering a certain motor performance during well-established everyday activities, such as preparing a simple meal, changed when additional (cognitive) tasks were performed. Within a healthy population, the probability of lower acceleration frequency patterns increases when people are asked to multitask. Cognitive decline due to aging or disease might yield even greater differences. |
| first_indexed | 2024-09-23T09:50:33Z |
| format | Article |
| id | mit-1721.1/110944 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:50:33Z |
| publishDate | 2017 |
| publisher | Springer-Verlag |
| record_format | dspace |
| spelling | mit-1721.1/1109442022-09-26T14:06:54Z A Bayesian Assessment of Real-World Behavior During Multitasking Fei, Joan Green, David A Hussain, Amir Howard, Newton Bergmann, Jeroen H. M. Massachusetts Institute of Technology. Media Laboratory Howard, Newton Bergmann, Jeroen H. M. Multitasking is common in everyday life, but its effect on activities of daily living is not well understood. Critical appraisal of performance for both healthy individuals and patients is required. Motor activities during meal preparation were monitored in healthy individuals with a wearable sensor network during single and multitask conditions. Motor performance was quantified by the median frequencies (fm) of hand trajectories and wrist accelerations. The probability that multitasking occurred based on the obtained motor information was estimated using a Naïve Bayes Model, with a specific focus on the single and triple loading conditions. The Bayesian probability estimator showed task distinction for the wrist accelerometer data at the high and low value ranges. The likelihood of encountering a certain motor performance during well-established everyday activities, such as preparing a simple meal, changed when additional (cognitive) tasks were performed. Within a healthy population, the probability of lower acceleration frequency patterns increases when people are asked to multitask. Cognitive decline due to aging or disease might yield even greater differences. 2017-08-15T13:56:21Z 2017-08-15T13:56:21Z 2017-08 2017-02 2017-08-13T03:20:16Z Article http://purl.org/eprint/type/JournalArticle 1866-9956 1866-9964 http://hdl.handle.net/1721.1/110944 Bergmann, Jeroen H.M. et al. “A Bayesian Assessment of Real-World Behavior During Multitasking.” Cognitive Computation 9, 4 (August 2017): 1-9 © 2017 The Author(s) https://orcid.org/0000-0002-8503-3973 en http://dx.doi.org/10.1007/s12559-017-9500-6 Cognitive Computation Creative Commons Attribution http://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer-Verlag Springer US |
| spellingShingle | Fei, Joan Green, David A Hussain, Amir Howard, Newton Bergmann, Jeroen H. M. A Bayesian Assessment of Real-World Behavior During Multitasking |
| title | A Bayesian Assessment of Real-World Behavior During Multitasking |
| title_full | A Bayesian Assessment of Real-World Behavior During Multitasking |
| title_fullStr | A Bayesian Assessment of Real-World Behavior During Multitasking |
| title_full_unstemmed | A Bayesian Assessment of Real-World Behavior During Multitasking |
| title_short | A Bayesian Assessment of Real-World Behavior During Multitasking |
| title_sort | bayesian assessment of real world behavior during multitasking |
| url | http://hdl.handle.net/1721.1/110944 https://orcid.org/0000-0002-8503-3973 |
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