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Peer-Reviewed Articles and Publications Featuring Notch Technology

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Comparison Among Standard Method, Dedicated Toolbox and Kinematic-Based Approach in Assessing Risk of Developing Upper Limb Musculoskeletal Disorders

ergonomics
Stefano Elio Lenzi, Carlo Emilio Standoli, Giuseppe Andreoni, Paolo Perego, Nicola Francesco Lopomo

OCRA (Occupational Repetitive Action) index is one of the most used method for supporting risk assessment in tasks requiring manual handling of low loads at high frequency. One of the main drawbacks of this method is that the operator analyses the activities by observing videos. This kind of procedure is inherently not objective and operator-dependent. To overcome these limitations, we developed a toolbox to support the analysis with contextual noting and wearable sensors kinematic data. Three expert operators were asked to evaluate seven videos with and without the aid of the developed toolbox. Results underlined a high inter (R2 mean 0.4) and intra-operator variability (posture time percentage and technical actions (TAs) count mean errors respectively 7.44%, 4 TAs) when using the only video-based approaches. On the contrary, research outcomes showed that the introduction of wearable device allow to overcome these issues and to reduce noticeably the evaluation time (−98%).

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A Software Toolbox to Improve Time-Efficiency and Reliability of an Observational Risk Assessment Method

ergonomics
Stefano Elio Lenzi, Carlo Emilio Standoli, Giuseppe Andreoni, Paolo Perego, Nicola Francesco Lopomo

OCRA is a standard risk assessment method addressing manual handling of low loads at high frequency. This method requires the operator to perform a video analysis checking kind and extension of the movements made by workers. The analyst has to take note about number of performed actions and joint angles amplitude. Often this turn out to be a poorly reliable and time-consuming operation because of the inherent 2D nature of the data. The main goal of this work was to design a software toolbox able to support the operator in collecting, organizing and analyzing the information to obtain the Checklist OCRA index in a more reliable and time-effective way. This toolbox presents three different GUIs to: (1) support the operator in counting the number of technical actions; (2) help the operator in determine the percentage of time in which the worker has an incorrect upper limb posture; (3) automatically perform posture analysis considering real 3D angles data acquired through an IMU-based movement analysis system. Preliminary analysis on reliability was performed on three different operators. Obtained findings confirmed our hypothesis; the automatic analysis, in particular, reduced significantly intra- and inter-operator variability thus making the analysis more objective and reliable. Further evaluations will include structured assessment including several operators with different expertise levels and collecting information about user experience (usability, GUI design, etc.) and overall performance compared to standards (operation time and results accuracy).

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SmartFall: A Smartwatch-Based Fall Detection System Using Deep Learning

healthcare
Taylor R. Mauldin, Marc E. Canby, Vangelis Metsis, Anne H. H. Ngu, Coralys Cubero Rivera

This paper presents SmartFall, an Android app that uses accelerometer data collected from a commodity-based smartwatch Internet of Things (IoT) device to detect falls. The smartwatch is paired with a smartphone that runs the SmartFall application, which performs the computation necessary for the prediction of falls in real time without incurring latency in communicating with a cloud server, while also preserving data privacy. We experimented with both traditional (Support Vector Machine and Naive Bayes) and non-traditional (Deep Learning) machine learning algorithms for the creation of fall detection models using three different fall datasets (Smartwatch, Notch, Farseeing). Our results show that a Deep Learning model for fall detection generally outperforms more traditional models across the three datasets. This is attributed to the Deep Learning model’s ability to automatically learn subtle features from the raw accelerometer data that are not available to Naive Bayes and Support Vector Machine, which are restricted to learning from a small set of extracted features manually specified. Furthermore, the Deep Learning model exhibits a better ability to generalize to new users when predicting falls, an important quality of any model that is to be successful in the real world. We also present a three-layer open IoT system architecture used in SmartFall, which can be easily adapted for the collection and analysis of other sensor data modalities (e.g., heart rate, skin temperature, walking patterns) that enables remote monitoring of a subject’s wellbeing.

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The Movement Undercommons: Movement Analysis as Meaning Making in a Time of Global Migrations

interactive art
Grisha Coleman, Brenda McCaffrey

While migration studies are generally approached in geographical/statistical/geo-political terms [time, histories, routes], this project considers migratory movement at the scale of individual human movement. movement as a marker of identity expressed through qualities of posture, rhythm, gesture, tempo, orientation. Each person’s movement is unique, an individual’s movement ‘fingerprint’, and this project seeks to reveal and honor the specific, fluid, complex qualities of a people in motion of body and location, while adding to a critical discourse surrounding issues of contemporary migration. This is a position paper describing the research framework behind a new project which proposes an exploration of movement and mobility amongst internal migratory populations within two pilot areas; South Africa and Greece. This work develops our previous work, creating a repository for a growing collection of highresolution motion-capture ‘portraits’. This repository will not only hold the source documentation of movement sequences, but also serve as an open platform for those recorded. It will become a space for discussion, creative interpretation, translation, annotation, and analysis. The repository opens a public space for artists, researchers, dancers, ethnographers, humanists, and somatic movement educators to respond and add diverse layers of meaning; creative interpretation, social and historical context, and technological and somatic analysis. Thus, we build an expandable platform for exploring the linguistics of movement through a range of responses.

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Interfacing Gestural Data from Instrumentalists

interactive art
Martin Jaroszewicz

This paper presents preliminary work on a system for capturing gestures from music instrumentalists. A saxophone player performed an étude from standard repertoire in two different manners: firstly, constraining their physical gestures to pro- duce sound and execute the written music; secondly, to exaggerate the gestures to include expressions of emotions. The author used a “non-invasive” way to capture the performance gesture using wearable IMU devices with sensor fusion. Using open source 3D creation software, the author extracted motion paths from the data generated by the performer. A 3D Kernel Density Estimation (KDE) algorithm was implemented to create a visualization of density of the trajectories of the head, left elbow and left hand. Analyzing the gestural space of a work of music to develop composition strategies when interfacing the machine and the performer in real time electroacoustic music is highlighted.

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The implementation of heart rate sensor and motion sensors based on internet of things for atlete performance monitoring.

sports
20. Sukaridhoto, S., Hidayat, M., Basuki, A., Arridha, R., Roy, A., Magfirah, T., Prasetyo, A., & Al Rasyid, U.

Indonesian achievements in the ASEAN Games continued to decline in achievement starting in 1962 with the acquisition of 51 medals and up to 2014 with the acquisition of 20 medals. The decline in achievement was due to the lack of athletic resources due to the absence of media that could record athletes' abilities in the field. Can record the athlete's performance before running, running and after running using the Heart Rate sensor and Motion Capture sensor...

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Implementation of Motion Capture System for Swimmer Athlete Monitoring

sports
Hidayat Yani, M. A., Bayu Aji, S., Ariyanti, I. F., Sukaridhoto, S., Zainuddin, M. A., & Basuki, A.

Swimming is one of the aquatic sports. Swimming is an effort to move (float or lift) all parts of the body to the surface of the water. Swimming is generally done without assistance equipment. Swimming is a sport that uses limbs, especially in the hands and feet to move in the water. In Indonesia, measuring the athlete's swimming movements is still manual, looking directly at the place of activity. This is a problem where the observations of each trainer are different so to evaluate the actions must be repeated activities, with this problem the researcher has made a tool to capture Athlete movements using the gyro sensor with communication via Bluetooth and displayed on an Android smart device.

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Analysis of swing tempo, swing rhythm, and functional swing plane slope in golf with a wearable inertial measurement unit sensor.

sports
Cheon, M., Khuyagbaatar, B., Yeom, J.-H., & Kim, Y. H.

Swing tempo, rhythm and swing plane are shown to be important in maintaining the performance. However, nearly all studies utilized optical motion capture system for the planar behavior of golf swings and the movement of the club. The primary aim of this study was to develop inertial measurement unit sensor-based swing motion analysis algorithm, and validate against an optical motion camera system by comparing the estimated clubhead trajectories during the golf swing. Then, the tempo, rhythm and functional swing plane were investigated using a validated wearable inertial sensor.

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As Light as Your Scent: Effects of Smell and Sound on Body Image Perception

human-computer interaction
Giada Brianza, Ana Tajadura-Jimenez , Emanuela Maggioni, Dario Pittera, Nadia Bianchi-Berthouze, and Marianna Obrist

As Light as Your Scent: Effects of Smell and Sound on Body Image Perception

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Context and Methods for Improved Velomobiles

sports
Stephen Nurse

This article discusses future transport emphasizing the aerodynamic cycles called velomobiles. Along with bicycles and ebikes, velomobiles are low energy transport which could displace cars as our commonly owned vehicles. Velomobiles are discussed in the light of emerging 3d printing, solar and structural battery technologies which could allow them and other cycles to be more useful and go further for less energy. Development and use of these technologies in velomobiles would benefit transport options and the technologies themselves, allowing beneficial and practical demonstrations in practical machines. Velomobiles using new technologies could be simpler and more relatable than cars and aeroplanes using the same technologies. The article aims to promote velomobiles and emerging solar, battery, and 3d printing technologies through their use in velomobiles. It highlights Australian researchers and manufacturers. Discussion includes the author's electric leaning trike which has timber panels replaceable by panels containing batteries or solar cells.

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Wireless Epidermal Six-Axis Inertial Measurement Units for Real-Time Joint Angle Estimation

electronics
Lee, J. K., Han, S. J., Kim, K., Kim, Y. H., & Lee, S.

Technological advances in wireless communications, miniaturized sensors, and low-power electronics have made it possible to implement integrated wireless body area networks (WBANs). These developments enable the applications of wireless wearable systems for diagnosis, health monitoring, rehabilitation, and dependency care. Across the current range of commercial wearable devices, the products are not firmly fixed to the human body. To minimize data error caused by movement of the human body and to achieve accurate measurements, it is essential to bring the wearable device close to the skin. This paper presents the implementation of a patch-type, six-axis inertial measurement unit (IMU) with wireless communication technology.

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