Research Papers - Department of Electrical and Electronic Engineering

Permanent URI for this collectionhttps://rda.sliit.lk/handle/123456789/679

Browse

Filters

2012 - 20133

Advanced Search

Filter by

Settings

Author: search.filters.author.Murray, ISubject: search.filters.subject.gyroscopic data

Search Results

Now showing 1 - 3 of 3
  • Thumbnail Image
    PublicationOpen Access
    Accurate Pedometer for Smartphones
    (2013) Jayalath, S; Abhayasinghe, N; Murray, I
    Accuracy of step counting is one of the main problems that exist in current Pedometers, especially when walking slowly on flat lands and performing different activities, such as climbing up and down stairs and walking on inclined planes. Although accelerometer based pedometers provide a reasonable accuracy when walking at higher speeds, the accuracy of them are not sufficient at slow walking speeds and performing different activities. This paper proposes a novel algorithm to detect steps using single-point gyroscopic sensors embedded in mobile devices. Preliminary analysis of data collected in different environments with the involvement of male and female volunteers indicated that gyroscope alone provides sufficient information necessary for accurate step detection. Algorithm was developed based on the gyroscopic data in conjunction with zero crossing and threshold detection techniques. The results proved that gyroscope based step detection algorithm provide a high accuracy when performing different activities and at slow paced walking.
  • Thumbnail Image
    PublicationOpen Access
    A novel approach for indoor localization using human gait analysis with gyroscopic data
    (2012 International Conference on Indoor Positioning and Indoor Navigation, 2012-11) Abhayasinghe, N; Murray, I
    — Way finding is one of the main difficulties that vision impaired people face, especially in indoor environments. Although Global Positioning System (GPS) based navigation is possible outdoors, the accuracy of GPS is not sufficient for indoor navigation and way finding. Most of the existing indoor localization and path finding techniques depend on additional infrastructure deployed in the environment. This paper proposes a novel technique for indoor localization based on human gait using single-point sensors embedded in mobile devices. It involves inertial sensors and other sensors such as magnetometer, generally embedded into the mobile devices. Progress made from data collection indicates that there is a better correlation of gyroscopic data than acceleration data to the gait of the person. Data was collected in different environments with the involvement of multiple male and female volunteers with no vision impairment or motor disability. The two carrying positions considered in this experiment were in the hip-pocket (pocket of the trouser) and clipped into the belt (hip). Various positioning experiments determined that a possible optimal location for the data gathering device was in the subject’s hip-pocket as compared to placement on the belt (hip region) as the movement of the thigh can be tracked when the device is placed in this position. It was also observed that the gyroscopic data can be used to identify different activities, such as walking on flat land, climbing up and down stairs and walking on inclined planes. Although the amplitude of the signal is small at the beginning and the end of the travel, the gyroscopic signal clearly identifies the step events. It is concluded that gyroscopic data gives promising results in indoor localization using gait analysis when the device is placed in the hip-pocket.
  • Thumbnail Image
    PublicationOpen Access
    A gyroscope based accurate pedometer algorithm
    (International Conference on Indoor Positioning and Indoor Navigation, 2013-10) Jayalath, S; Abhayasinghe, N; Murray, I
    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.