Can Smartwatches Replace Smartphones for Posture Tracking?
This paper introduces a human posture tracking platform to identify the human postures of sitting, standing or lying down, based on a smartwatch. This work develops such a system as a proof-of-concept study to investigate a smartwatch’s ability to be used in future remote health monitoring systems a...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2015-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/15/10/26783 |
| _version_ | 1811302078111285248 |
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| author | Bobak Mortazavi Ebrahim Nemati Kristina VanderWall Hector G. Flores-Rodriguez Jun Yu Jacinta Cai Jessica Lucier Arash Naeim Majid Sarrafzadeh |
| author_facet | Bobak Mortazavi Ebrahim Nemati Kristina VanderWall Hector G. Flores-Rodriguez Jun Yu Jacinta Cai Jessica Lucier Arash Naeim Majid Sarrafzadeh |
| author_sort | Bobak Mortazavi |
| collection | DOAJ |
| description | This paper introduces a human posture tracking platform to identify the human postures of sitting, standing or lying down, based on a smartwatch. This work develops such a system as a proof-of-concept study to investigate a smartwatch’s ability to be used in future remote health monitoring systems and applications. This work validates the smartwatches’ ability to track the posture of users accurately in a laboratory setting while reducing the sampling rate to potentially improve battery life, the first steps in verifying that such a system would work in future clinical settings. The algorithm developed classifies the transitions between three posture states of sitting, standing and lying down, by identifying these transition movements, as well as other movements that might be mistaken for these transitions. The system is trained and developed on a Samsung Galaxy Gear smartwatch, and the algorithm was validated through a leave-one-subject-out cross-validation of 20 subjects. The system can identify the appropriate transitions at only 10 Hz with an F-score of 0.930, indicating its ability to effectively replace smart phones, if needed. |
| first_indexed | 2024-04-13T07:21:26Z |
| format | Article |
| id | doaj.art-bf1a5a73a9c74a93818297a56f71eb50 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-13T07:21:26Z |
| publishDate | 2015-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-bf1a5a73a9c74a93818297a56f71eb502022-12-22T02:56:37ZengMDPI AGSensors1424-82202015-10-011510267832680010.3390/s151026783s151026783Can Smartwatches Replace Smartphones for Posture Tracking?Bobak Mortazavi0Ebrahim Nemati1Kristina VanderWall2Hector G. Flores-Rodriguez3Jun Yu Jacinta Cai4Jessica Lucier5Arash Naeim6Majid Sarrafzadeh7Computer Science Department, University of California, Los Angeles, Los Angeles, CA 90095, USADepartment of Electrical Engineering, University of California, Los Angeles, Los Angeles, CA 90095, USASchool of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USAComputer Science Department, El Camino College, Torrance, CA 90506, USAComputer Science Department, University of Alabama Birmingham, Birmingham, AL 35233, USASchool of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USASchool of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USAComputer Science Department, University of California, Los Angeles, Los Angeles, CA 90095, USAThis paper introduces a human posture tracking platform to identify the human postures of sitting, standing or lying down, based on a smartwatch. This work develops such a system as a proof-of-concept study to investigate a smartwatch’s ability to be used in future remote health monitoring systems and applications. This work validates the smartwatches’ ability to track the posture of users accurately in a laboratory setting while reducing the sampling rate to potentially improve battery life, the first steps in verifying that such a system would work in future clinical settings. The algorithm developed classifies the transitions between three posture states of sitting, standing and lying down, by identifying these transition movements, as well as other movements that might be mistaken for these transitions. The system is trained and developed on a Samsung Galaxy Gear smartwatch, and the algorithm was validated through a leave-one-subject-out cross-validation of 20 subjects. The system can identify the appropriate transitions at only 10 Hz with an F-score of 0.930, indicating its ability to effectively replace smart phones, if needed.http://www.mdpi.com/1424-8220/15/10/26783activity recognitionsmartwatchposture trackingwireless healthmachine learningembedded medical systems |
| spellingShingle | Bobak Mortazavi Ebrahim Nemati Kristina VanderWall Hector G. Flores-Rodriguez Jun Yu Jacinta Cai Jessica Lucier Arash Naeim Majid Sarrafzadeh Can Smartwatches Replace Smartphones for Posture Tracking? Sensors activity recognition smartwatch posture tracking wireless health machine learning embedded medical systems |
| title | Can Smartwatches Replace Smartphones for Posture Tracking? |
| title_full | Can Smartwatches Replace Smartphones for Posture Tracking? |
| title_fullStr | Can Smartwatches Replace Smartphones for Posture Tracking? |
| title_full_unstemmed | Can Smartwatches Replace Smartphones for Posture Tracking? |
| title_short | Can Smartwatches Replace Smartphones for Posture Tracking? |
| title_sort | can smartwatches replace smartphones for posture tracking |
| topic | activity recognition smartwatch posture tracking wireless health machine learning embedded medical systems |
| url | http://www.mdpi.com/1424-8220/15/10/26783 |
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