Anna Åkerberg

Investigation of the validity and reliability of a smartphone pedometer application

Abstract The aim of this study was to investigate the validity and measurement agreement of a smartphone pedometer application and a traditional pedometer, both compared to manual step count, in six environments. The study also examined the relative reliability of two positions of the smartphone pedometer application in the six environments. Twenty participants carried two smartphones (iPhone 4S) with the same pedometer application (Pedometer FREE GPS+) in two device positions together with a traditional pedometer (Yamax LS2000) while walking in six environments. The pedometer application in the chest position (app chest) differed significantly from the manual step count when walking uphill (p = 0.003), the application in the trouser (pants) position (app pants) differed for downhill (p = 0.001) and the traditional pedometer (trad ped) differed upstairs (p = 0.007). The measurement agreement was high for app pants uphill, app chest downhill and trad ped downstairs. The relative reliability was fair for app chest, but poor for app pants. In conclusion, the pedometer application and traditional pedometer were valid for step self-monitoring in some environments, and the measurement agreement compared to manual step count was mainly medium to high. The relative reliability for the smartphone pedometer application was partly acceptable. Smartphones could be useful in some environments for physical activity self-monitoring.

Innovations to Control the Environment for Persons with Movement Disorders: Support in Home Care

This review focuses on recent innovations and patents with the aim to allow people with movement disorders to control their environment. This particularly includes different technologies for input devices to control computers and other electronic equipment used by persons with movement disorders, enabling the empowerment of this user group. The control of such devices can be the key to social inclusion and mean improved social contact with others, access of information or possibility to work. In this paper, several patents and innovations are described that enable such control, divided into the groups; Input devices in form of switches and touchscreens, Inertia and inclinometer sensors, Voice control and Gesture control. Also methods allowing monitoring and classification of physical activity, i.e. assisting to alarm in case of a fall and systems assisting in rehabilitation at home, are included, as are video games aimed to promote physical activity.

Technologies for physical activity self-monitoring: a study of differences between users and non-users

Background Different kinds of physical activity (PA) self-monitoring technologies are used today to monitor and motivate PA behavior change. The user focus is essential in the development process of this technology, including potential future users such as representatives from the group of non-users. There is also a need to study whether there are differences between the groups of users and non-users. The aims of this study were to investigate possible differences between users and non-users regarding their opinions about PA self-monitoring technologies and to investigate differences in demographic variables between the groups. Materials and methods Participants were randomly selected from seven municipalities in central Sweden. In total, 107 adults responded to the Physical Activity Products Questionnaire, which consisted of 22 questions. Results Significant differences between the users and non-users were shown for six of the 20 measurement-related items: measures accurately (p=0.007), measures with high precision (p=0.024), measures distance (p=0.020), measures speed (p=0.003), shows minutes of activity (p=0.004), and shows geographical position (p=0.000). Significant differences between the users and non-users were also found for two of the 29 encouragement items: measures accurately (p=0.001) and has long-term memory (p=0.019). Significant differences between the groups were also shown for level of education (p=0.030) and level of physical exercise (p=0.037). Conclusion With a few exceptions, the users and the non-users in this study had similar opinions about PA self-monitoring technologies. Because this study showed significant differences regarding level of education and level of physical exercise, these demographic variables seemed more relevant to investigate than differences in opinions about the PA self-monitoring technologies.

Walking Intensity Estimation with a Portable Pedobarography System

The aim of this pilot study was to investigate the possibility to find a correlation between the output from a portable pedobarography system and the walking intensity expressed as walking speed. The system uses shoe insoles with force sensing resistors and wireless transmission of the data via Bluetooth. The force-time integral, at the toe-off phase of the step, for the force sensors in the forward part of the right foot was used to measure impulse data for 10 subjects performing walks in three different walking speeds. This data was then corrected by multiplication with the step frequency. This pilot study indicates that the portable pedobarography system output shows a linear relationship with the walking intensity expressed as walking speed on an individual level.

Heart rate measurement as a tool to quantify sedentary behavior.

Sedentary work is very common today. The aim of this pilot study was to attempt to differentiate between typical work situations and to investigate the possibility to break sedentary behavior, based on physiological measurement among office workers. Ten test persons used one heart rate based activity monitor (Linkura), one pulse oximeter device (Wrist) and one movement based activity wristband (Fitbit Flex), in different working situations. The results showed that both heart rate devices, Linkura and Wrist, were able to detect differences in heart rate between the different working situations (resting, sitting, standing, slow walk and medium fast walk). The movement based device, Fitbit Flex, was only able to separate differences in steps between slow walk and medium fast walk. It can be concluded that heart rate measurement is a promising tool for quantifying and separating different working situations, such as sitting, standing and walking.

Accuracy in pedometers: dependent on the technology for measurement?

Today, there are a variety of pedometers available based on different technologies. The aim of this study was to investigate step measurement accuracy regarding two different pedometer technologies, spring-suspended lever arm and accelerometers, in six walking environments, compared to a reference method. Descriptive data indicates that the spring-suspended lever arm pedometer had the largest SD and underestimated the steps in five out of six walking environments. The ANOVA showed that both pedometer technologies performed accurate measurements in one of the walking environments. However, none of the pedometer technologies performed accurate step measurements in all six walking environments.

Evaluation of the IngVaL Pedobarography System for Monitoring of Walking Speed

Objectives Walking speed is an important component of movement and is a predictor of health in the elderly. Pedobarography, the study of forces acting between the plantar surface of the foot and a supporting surface, is an approach to estimating walking speed even when no global positioning system signal is available. The developed portable system, Identifying Velocity and Load (IngVaL), is a cost effective alternative to commercially available pedobarography systems because it only uses three force sensing resistors. In this study, the IngVaL system was evaluated. The three variables investigated in this study were the sensor durability, the proportion of analyzable steps, and the linearity between the system output and the walking speed. Methods Data was collected from 40 participants, each of whom performed five walks at five different self-paced walking speeds. The linearity between the walking speed and step frequency measured with R2 values was compared for the walking speed obtained ‘A’ only using amplitude data from the force sensors, ‘B’ that obtained only using the step frequency, and ‘C’ that obtained by combining amplitude data for each of the 40 test participants. Results Improvement of the wireless data transmission increased the percentage of analyzable steps from 83.1% measured with a prototype to 96.6% for IngVaL. The linearity comparison showed that the methods A, B, and C were accurate for 2, 15, and 23 participants, respectively. Conclusions Increased sensor durability and a higher percentage of analyzed steps indicates that IngVaL is an improvement over the prototype system. The combined strategy of amplitude and step frequency was confirmed as the most accurate method.