John McCormick

Teaching a Digital Performing Agent: Artificial Neural Network and Hidden Markov Model for recognising and performing dance movement

Publisher: ACM

Date: 16-06-2014

DOI: 10.1145/2617995.2618008

Aurora Australis Ultimo Choro

Publisher: ACM

Date: 14-12-2021

DOI: 10.1145/3476123.3487883

Touching space: Using motion capture and stereo projection to create a Virtual haptics of dance

Publisher: MIT Press - Journals

Date: 08-2010

DOI: 10.1162/LEON_A_00009

Abstract: This paper describes the work of a group of artists in Australia who used real-time motion capture and 3D stereo projection to create a large-scale performance environment in which dancers seemed to “touch” the volume. This project re-versions Suzanne Langer's 1950s philosophy of dance as “virtual force” to realize the idea of a “virtual haptics” of dance that extends the dancer's physical agency literally across and through the surrounding spatial volume. The project presents a vision of interactive dance performance that “touches” space by visualizing kinematics as intentionality and agency. In doing so, we suggest the possibility of new kinds of human-computer interfaces that emphasize touch as embodied, nuanced agency that is mediated by the subtle qualities of whole-body movement, in addition to more goal-oriented, task-based gestures such as pointing or clicking.

Feels Like Dancing: Motion capture driven haptic interface as an added sensory experience for dance viewing

Publisher: No publisher found

Date: 2018

DOI: 10.1162/LEON\_A\_01689

Self-reported prevalence of injury and discomfort experienced by surgeons performing traditional and robot-assisted laparoscopic surgery: a meta-analysis demonstrating the value of RALS for surgeons

Publisher: Springer Science and Business Media LLC

Date: 24-07-2020

DOI: 10.1007/S00464-020-07810-2

Child in the wild

Publisher: ACM

Date: 22-06-2017

DOI: 10.1145/3059454.3059509

Validation of 3-Space Wireless Inertial Measurement Units Using an Industrial Robot

Publisher: MDPI AG

Date: 15-10-2021

DOI: 10.3390/S21206858

Abstract: Inertial Measurement Units (IMUs) are beneficial for motion tracking as, in contrast to most optical motion capture systems, IMU systems do not require a dedicated lab. However, IMUs are affected by electromagnetic noise and may exhibit drift over time it is therefore common practice to compare their performance to another system of high accuracy before use. The 3-Space IMUs have only been validated in two previous studies with limited testing protocols. This study utilized an IRB 2600 industrial robot to evaluate the performance of the IMUs for the three sensor fusion methods provided in the 3-Space software. Testing consisted of programmed motion sequences including 360° rotations and linear translations of 800 mm in opposite directions for each axis at three different velocities, as well as static trials. The magnetometer was disabled to assess the accuracy of the IMUs in an environment containing electromagnetic noise. The Root-Mean-Square Error (RMSE) of the sensor orientation ranged between 0.2° and 12.5° across trials average drift was 0.4°. The performance of the three filters was determined to be comparable. This study demonstrates that the 3-Space sensors may be utilized in an environment containing metal or electromagnetic noise with a RMSE below 10° in most cases.

Recognition: Combining human interaction and a digital performing agent

Publisher: ACM

Date: 09-04-2014

DOI: 10.1145/2617841.2620707

Trouble tower game demo

Publisher: ACM

Date: 30-09-2013

DOI: 10.1145/2513002.2513035

Feels Like Dancing: Motion Capture-Driven Haptic Interface as an Added Sensory Experience for Dance Viewing

Publisher: MIT Press - Journals

Date: 02-2020

DOI: 10.1162/LEON_A_01689

Abstract: This paper describes a system for delivering movement information from a dance performance using a multisensory approach that includes visual, sonic and haptic information. The work builds on previous research into interpreting dance as haptic information for blind, deaf-blind and vision-impaired audience members. This current work is aimed at a general audience, with haptic information being one of a number of sensory experiences of the dance. A prototype haptic device has been developed for use in dance performance research.

What robots learn from performative relationships and interactive performance

Publisher: Bloomsbury Academic

Date: 2022

DOI: 10.5040/9781501361289.CH-012

Touching space: Using motion capture and stereo projection to create a virtual haptics of dance

Publisher: ACM

Date: 26-07-2010

DOI: 10.1145/1836786.1836791

A Recommender System of Extended Reality Experiences

Publisher: ACM

Date: 08-02-2020

DOI: 10.1145/3383812.3383839

Navigating control and illusion: functional interactivity versus ‘faux-interactivity’ in transmedia dance performance

Publisher: Informa UK Limited

Date: 02-01-2016

DOI: 10.1080/14794713.2016.1161955

Duet: Improvising spatial dialogues with an artificially intelligent agent

Publisher: ACM

Date: 08-08-2015

DOI: 10.1145/2788940.2788952

Oncheon: Learning to perform motion trails for virtual spaces

Publisher: BCS Learning & Development

Date: 2020

DOI: 10.14236/EWIC/EVA2020.51

Muscle activation during traditional laparoscopic surgery compared with robot-assisted laparoscopic surgery: a meta-analysis

Publisher: Springer Science and Business Media LLC

Date: 03-10-2019

DOI: 10.1007/S00464-019-07161-7

Abstract: The repetitive and forceful motions used by operating surgeons increase the risk of developing musculoskeletal disorders. Most ergonomists consider the surgical environment to be incredibly harsh for its workers. Traditional Laparoscopic Surgery (TLS) in particular has a number of physical and mental challenges associated with it, and while Robotic-Assisted Laparoscopic Surgery (RALS) provides several features that improve upon TLS, some surgeons have still reported musculoskeletal symptoms they attribute to RALS. In this paper, we endeavored to systematically review muscle activation for both TLS and RALS, to compare the modalities and present the results as a meta-analysis. A literature search was conducted using Pubmed, Embase, and Cochrane databases in November 2018 with the following inclusion criteria: full text was available in English, the paper contained original data, EMG was one of the primary measurement techniques, and the paper included EMG data for both TLS and RALS. Results from studies were compared using standardized mean difference analysis. A total of 379 papers were found, and through screening ten were selected for inclusion. S le populations ranged from 1 to 31 surgeons, and a variety of study designs and metrics were used between studies. The biceps were the only muscle group that consistently and significantly demonstrated lower muscle activation for RALS for all included studies. The results may support the belief that RALS is ergonomically superior to TLS, shown through generally lower muscle activation scores. However, these results must be interpreted with caution due to the heterogeneity between the studies and multiple potential sources for bias within studies. This analysis would be strengthened with a higher number of homogenous, high-quality studies examining larger s le sizes.

Eve of Dust

Publisher: ACM

Date: 04-12-2018

DOI: 10.1145/3282805.3282807

Sensitivity of the Cherenkov Telescope Array for probing cosmology and fundamental physics with gamma-ray propagation

Publisher: IOP Publishing

Date: 23-02-2021

DOI: 10.1088/1475-7516/2021/02/048

Haptically-enabled dance visualisation framework for deafblind-folded audience and artists

Publisher: IEEE

Date: 10-2016

DOI: 10.1109/SMC.2015.89

Deakin University

Location: Australia

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Swinburne University Of Technology

Location: Australia

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Industrial Transformation Training Centres - Grant ID: IC200100001

Start Date: 08-2021

End Date: 08-2026

Amount: $4,879,415.00

Funder: Australian Research Council

Linkage Infrastructure, Equipment And Facilities - Grant ID: LE170100066

Start Date: 01-2017

End Date: 10-2018

Amount: $350,000.00

Funder: Australian Research Council

Discovery Projects - Grant ID: DP220102118

Start Date: 12-2022

End Date: 12-2025

Amount: $464,000.00

Funder: Australian Research Council