A two-stage approach to bring the postural assessment to masses: The KISS-Health Project

Bortone, Ilaria; Argentiero, Alberto; Agnello, Nadia; Sabato, Stefano Santo; Bucciero, Alberto

doi:10.1109/bhi.2014.6864380

Cited by 6 publications

(5 citation statements)

References 9 publications

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“…Most of the studies did not state any medical condition that resulted in posture abnormality. However, in [47], Parkinson's disease was stated, and in [56], a case of chronic traumatic brain injury was present. In [50,58], patients with suspected multiple scoliosis were also assessed for posture abnormality.…”

Section: Resultsmentioning

confidence: 99%

A Review on the Use of Microsoft Kinect for Gait Abnormality and Postural Disorder Assessment

Bawa

Banitsas

Abbod

2021

Journal of Healthcare Engineering

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Gait and posture studies have gained much prominence among researchers and have attracted the interest of clinicians. The ability to detect gait abnormality and posture disorder plays a crucial role in the diagnosis and treatment of some diseases. Microsoft Kinect is presented as a noninvasive sensor essential for medical diagnostic and therapeutic purposes. There are currently no relevant studies that attempt to summarise the existing literature on gait and posture abnormalities using Kinect technology. The purpose of this study is to critically evaluate the existing research on gait and posture abnormalities using the Kinect sensor as the main diagnostic tool. Our studies search identified 458 for gait abnormality, 283 for posture disorder of which 26 studies were included for gait abnormality, and 13 for posture. The results indicate that Kinect sensor is a useful tool for the assessment of kinematic features. In conclusion, Microsoft Kinect sensor is presented as a useful tool for gait abnormality, postural disorder analysis, and physiotherapy. It can also help track the progress of patients who are undergoing rehabilitation.

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Section: Resultsmentioning

confidence: 99%

A Review on the Use of Microsoft Kinect for Gait Abnormality and Postural Disorder Assessment

Bawa

Banitsas

Abbod

2021

Journal of Healthcare Engineering

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“…The research team is currently working on the extension of the work by increasing the statistical sample both by number and by age group involving other schools in the pilot project. Furthermore, the temporal analysis will be extended in relation to the quantitative assessment of postural diseases that the KISS-Health Project will execute in the School with the Mobile Diagnostic Lab realized under this social innovation initiative [10,11]. To our knowledge, no previous studies have investigated the role of introducing educational technologies to vehicle preventive postural interventions.…”

Section: Perspectives and On-going Workmentioning

confidence: 99%

“…The research team approached the School Principal of the "Materdona -Moro" Secondary School in Mesagne, Italy, to introduce the KISS-Health Project (Knowledge Intensive Social Services for Health) and the opportunity to implement a school-based postural education program, called PoSE Project (Postural Education at School), to avoid the possible negative physical effects of retained bad posture. The KISS-Health has adopted recent developments in gesturecapture technologies, in particular the Microsoft Kinect System, to recreate a Mobile Diagnostic Lab able to evaluate postural diseases [10,11]. Furthermore, the KISS-Health aims to introduce in the schools the idea of "Technological Learning", which is poised to become an even more important determinant of growth through its impact on innovation and the Kinect has the potential to facilitate the process.…”

Section: Introductionmentioning

confidence: 99%

The PoSE Project: the Potential of Technological Learning for Postural Education in Schoolchildren

Bortone¹,

Agnello²,

Argentiero³

et al. 2015

EAI Endorsed Transactions on e-Learning

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Back pain in children and adolescents is quite common, so developing preventive strategies for back pain is highly desirable. This article describes a planned school-based postural education project (PoSE) to promote healthy behaviors among middle school students and their families and to moderate postural diseases. As first s tep, w e e valuated w hich a spects o f p ostural b ehaviors w ere i ntegrated i n c hildren's l ifestyle through a questionnaire. Then, the educational program consisted of interactive lessons on back posture and good principles both in class and at home. A participatory approach was used to evaluate attempts to involve all who have a stake in outcomes in order to take action and effect change. The strength of the participatory approach used in this study lies in the contribution to empowerment social change.

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“…As we are living in the 21st century and people are using a smartphone for their convenience. First, we need to define different sitting postures as discussed in previous literature, such as forward position, middle position, or backward position, forward sitting posture, reclined sitting posture, slumped sitting posture, laterally tilted left or right sitting posture, arm back leaning, right over left, twist left, poking chin, arm learning, crossed legs right over left or left over right sitting posture and postures in school children [ 18 , 27 , 28 , 29 , 30 , 31 , 32 , 33 ]. The proposed study covered five different sitting postures, which are illustrated in Figure 1 .…”

Section: Introductionmentioning

confidence: 99%

Smartphone-Based Human Sitting Behaviors Recognition Using Inertial Sensor

Sinha

Patro

Pławiak

et al. 2021

Sensors

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At present, people spend most of their time in passive rather than active mode. Sitting with computers for a long time may lead to unhealthy conditions like shoulder pain, numbness, headache, etc. To overcome this problem, human posture should be changed for particular intervals of time. This paper deals with using an inertial sensor built in the smartphone and can be used to overcome the unhealthy human sitting behaviors (HSBs) of the office worker. To monitor, six volunteers are considered within the age band of 26 ± 3 years, out of which four were male and two were female. Here, the inertial sensor is attached to the rear upper trunk of the body, and a dataset is generated for five different activities performed by the subjects while sitting in the chair in the office. Correlation-based feature selection (CFS) technique and particle swarm optimization (PSO) methods are jointly used to select feature vectors. The optimized features are fed to machine learning supervised classifiers such as naive Bayes, SVM, and KNN for recognition. Finally, the SVM classifier achieved 99.90% overall accuracy for different human sitting behaviors using an accelerometer, gyroscope, and magnetometer sensors.

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A two-stage approach to bring the postural assessment to masses: The KISS-Health Project

Cited by 6 publications

References 9 publications

A Review on the Use of Microsoft Kinect for Gait Abnormality and Postural Disorder Assessment

A Review on the Use of Microsoft Kinect for Gait Abnormality and Postural Disorder Assessment

The PoSE Project: the Potential of Technological Learning for Postural Education in Schoolchildren

Smartphone-Based Human Sitting Behaviors Recognition Using Inertial Sensor

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