ReviewSensors (Basel, Switzerland)2025
Wireless Inertial Measurement Units in Performing Arts.
Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inertial Measurement Units (IMUs), which embed several sensors (accelerometers, gyroscopes, magnetometers) are employed by musicians and performers to control sound, music, or lighting on stage. In particular, wireless IMU systems in the performing arts require particular attention due to strict requirements regarding streaming sample rate, latency, power consumption, and programmability. This article presents a review of systems developed in this context at IRCAM as well as in other laboratories and companies, highlighting specificities in terms of sensing, communication, performance, digital processing, and usage. Although basic IMUs are now widely integrated into IoT systems and smartphones, the availability of complete commercial wireless systems that meet the constraints of the performing arts remains limited. For this reason, a review of systems used in performing Arts provides exemplary use cases that may also be relevant to other applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.