A Gyroscope Based Accurate Pedometer Algorithm
Accurate step counting is important in pedometer based indoor localization. Existing step detection techniques are not sufficiently accurate, especially at low walking speeds that are commonly observed when navigating unfamiliar environments. This is more critical when vision impaired indoor navigat...
| Main Authors: | , , |
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| Format: | Conference Paper |
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N/A
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/14986 |
| _version_ | 1848748770475376640 |
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| author | Jayalath, S. Abhayasinghe, Nimsiri Murray, Iain |
| author2 | N/A |
| author_facet | N/A Jayalath, S. Abhayasinghe, Nimsiri Murray, Iain |
| author_sort | Jayalath, S. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Accurate step counting is important in pedometer based indoor localization. Existing step detection techniques are not sufficiently accurate, especially at low walking speeds that are commonly observed when navigating unfamiliar environments. This is more critical when vision impaired indoor navigation is considered due to the fact that they have relatively low walking speeds. Almost all existing pedometer techniques use accelerometer data to identify steps, which is not very accurate at low walking speeds. This paper describes a gyroscope based pedometer algorithm implemented in a smartphone. The smartphone is placed in the pocket of the trouser, which is a usual carrying position of the mobile phone. The gyroscope sensor data is used for the identification of steps. The algorithm was designed to demand minimal computational resources so that it can be easily implemented in an embedded platform. Raw data from the sensor are filtered using a 6th order Butterworth filter for noise reduction. This is then sent though a zero crossing detector which identifies the steps. A minimum delay between two consecutive zero crossings was used to avoid fluctuations being counted and peak detection was used to validate steps. The algorithm has a calibration mode, in which the absolute minimum swing of data is learnt to set the threshold. This approach demonstrated accuracies above 96% even at slow walking speeds on flat land, above 95% when walking up/down hills and above 90% when going up/down stairs. This has supported the concept that the gyroscope can be used efficiently in step identification for indoor positioning and navigation systems. |
| first_indexed | 2025-11-14T07:10:19Z |
| format | Conference Paper |
| id | curtin-20.500.11937-14986 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:10:19Z |
| publishDate | 2013 |
| publisher | N/A |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-149862017-11-02T06:02:15Z A Gyroscope Based Accurate Pedometer Algorithm Jayalath, S. Abhayasinghe, Nimsiri Murray, Iain N/A pedometer algorithms localization and navigation vision impaired navigation step detection single point sensors gyroscopic data Accurate step counting is important in pedometer based indoor localization. Existing step detection techniques are not sufficiently accurate, especially at low walking speeds that are commonly observed when navigating unfamiliar environments. This is more critical when vision impaired indoor navigation is considered due to the fact that they have relatively low walking speeds. Almost all existing pedometer techniques use accelerometer data to identify steps, which is not very accurate at low walking speeds. This paper describes a gyroscope based pedometer algorithm implemented in a smartphone. The smartphone is placed in the pocket of the trouser, which is a usual carrying position of the mobile phone. The gyroscope sensor data is used for the identification of steps. The algorithm was designed to demand minimal computational resources so that it can be easily implemented in an embedded platform. Raw data from the sensor are filtered using a 6th order Butterworth filter for noise reduction. This is then sent though a zero crossing detector which identifies the steps. A minimum delay between two consecutive zero crossings was used to avoid fluctuations being counted and peak detection was used to validate steps. The algorithm has a calibration mode, in which the absolute minimum swing of data is learnt to set the threshold. This approach demonstrated accuracies above 96% even at slow walking speeds on flat land, above 95% when walking up/down hills and above 90% when going up/down stairs. This has supported the concept that the gyroscope can be used efficiently in step identification for indoor positioning and navigation systems. 2013 Conference Paper http://hdl.handle.net/20.500.11937/14986 N/A restricted |
| spellingShingle | pedometer algorithms localization and navigation vision impaired navigation step detection single point sensors gyroscopic data Jayalath, S. Abhayasinghe, Nimsiri Murray, Iain A Gyroscope Based Accurate Pedometer Algorithm |
| title | A Gyroscope Based Accurate Pedometer Algorithm |
| title_full | A Gyroscope Based Accurate Pedometer Algorithm |
| title_fullStr | A Gyroscope Based Accurate Pedometer Algorithm |
| title_full_unstemmed | A Gyroscope Based Accurate Pedometer Algorithm |
| title_short | A Gyroscope Based Accurate Pedometer Algorithm |
| title_sort | gyroscope based accurate pedometer algorithm |
| topic | pedometer algorithms localization and navigation vision impaired navigation step detection single point sensors gyroscopic data |
| url | http://hdl.handle.net/20.500.11937/14986 |