Abstract:Smartphones are increasingly incorporated with features such as sensors and high resolution cameras that empower their capabilities, enabling their use for varied activities including human posture assessments. Previous reviews have discussed methods used in postural assessment but none of them focused exclusively on mobile applications. This paper systematically reviews mobile applications proposed for analyzing human posture based on alignment of the body in the sagittal and coronal plane. The main digital l… Show more
“…Limited numbers of mobile apps for posture assessment have demonstrated reliability and validity. The mobile apps use different methodologies such as using markers, sensors, and photographs, and have some advantages and disadvantages when compared to each other [ 12 ]. For example, some apps are sensor based (accelerometer or gyroscope), and they were mostly developed to assess spinal orientation such as lordosis and kyphosis [ 30 – 32 ].…”
Section: Discussionmentioning
confidence: 99%
“…The angles and translations such as tilted positions of the body segments are assessed by image-based solutions such the app in the present study. The PostureScreen Mobile (PSM) is the most cited posture assessment app based on image obtained from photos in the related literature among these apps [ 12 ]. As Fizyoprint has the similar technological platform with PSM, we discuss our results mostly with the literature investigating the reliability and validity of PSM.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, 11 of 13 apps were classified as sensor-based (accelerometer or gyroscope) apps that have diverse approaches such as using assessment of radiographs [ 21 ] or direct contact with the body of patients [ 12 , 22 ]. Actually, most of the image-based solutions not only provide posture assessment for spinal orientation but also include other regions of the body by avoiding physically contact with patient and minimizing patients’ exposure to radiation [ 12 ]. However, up to our knowledge, there are still limited numbers of mobile apps for posture assessment of full body segments.…”
Section: Introductionmentioning
confidence: 99%
“…Visual inspection is a commonly used assessment method in the clinical settings, but visual inspection is lacking of scientific validation; it is highly prone to bias [10]. The literature reports a range of quantitative postural assessment techniques from the use of simple goniometerbased measurements to three-dimensional imaging technologies which are more objective measurements than visual inspection [11,12]. However, they have some advantages and disadvantages when compared with each other.…”
“…Limited numbers of mobile apps for posture assessment have demonstrated reliability and validity. The mobile apps use different methodologies such as using markers, sensors, and photographs, and have some advantages and disadvantages when compared to each other [ 12 ]. For example, some apps are sensor based (accelerometer or gyroscope), and they were mostly developed to assess spinal orientation such as lordosis and kyphosis [ 30 – 32 ].…”
Section: Discussionmentioning
confidence: 99%
“…The angles and translations such as tilted positions of the body segments are assessed by image-based solutions such the app in the present study. The PostureScreen Mobile (PSM) is the most cited posture assessment app based on image obtained from photos in the related literature among these apps [ 12 ]. As Fizyoprint has the similar technological platform with PSM, we discuss our results mostly with the literature investigating the reliability and validity of PSM.…”
Section: Discussionmentioning
confidence: 99%
“…Furthermore, 11 of 13 apps were classified as sensor-based (accelerometer or gyroscope) apps that have diverse approaches such as using assessment of radiographs [ 21 ] or direct contact with the body of patients [ 12 , 22 ]. Actually, most of the image-based solutions not only provide posture assessment for spinal orientation but also include other regions of the body by avoiding physically contact with patient and minimizing patients’ exposure to radiation [ 12 ]. However, up to our knowledge, there are still limited numbers of mobile apps for posture assessment of full body segments.…”
Section: Introductionmentioning
confidence: 99%
“…Visual inspection is a commonly used assessment method in the clinical settings, but visual inspection is lacking of scientific validation; it is highly prone to bias [10]. The literature reports a range of quantitative postural assessment techniques from the use of simple goniometerbased measurements to three-dimensional imaging technologies which are more objective measurements than visual inspection [11,12]. However, they have some advantages and disadvantages when compared with each other.…”
“…These include attempts to augment or replace existing tools with modern technologies. The most recent trend in diagnosis support is to use sensors and cameras built into smartphones [ 17 ]. Modern posture measurement tools are sophisticated systems that use a variety of measurement techniques.…”
Postural disorders, their prevention, and therapies are still growing modern problems. The currently used diagnostic methods are questionable due to the exposure to side effects (radiological methods) as well as being time-consuming and subjective (manual methods). Although the computer-aided diagnosis of posture disorders is well developed, there is still the need to improve existing solutions, search for new measurement methods, and create new algorithms for data processing. Based on point clouds from a Time-of-Flight camera, the presented method allows a non-contact, real-time detection of anatomical landmarks on the subject’s back and, thus, an objective determination of trunk surface metrics. Based on a comparison of the obtained results with the evaluation of three independent experts, the accuracy of the obtained results was confirmed. The average distance between the expert indications and method results for all landmarks was 27.73 mm. A direct comparison showed that the compared differences were statically significantly different; however, the effect was negligible. Compared with other automatic anatomical landmark detection methods, ours has a similar accuracy with the possibility of real-time analysis. The advantages of the presented method are non-invasiveness, non-contact, and the possibility of continuous observation, also during exercise. The proposed solution is another step in the general trend of objectivization in physiotherapeutic diagnostics.
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