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Miriam Zisook

dblp:135/8550 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2013
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Wearable and physiological sensing · 56% Health and well-being technologies · 44%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Wearable and physiological sensing › motion sensing
wearable motion sensing
0.212013
Soft wearable motion sensing suit for lower limb biomechanics measurements · ICRA 2013
Wearable and physiological sensing
strain sensor
0.012013
Soft wearable motion sensing suit for lower limb biomechanics measurements · ICRA 2013

Methods — techniques the papers use, named apart from their topics

hyperelastic strain sensing · 0.2calibration · 0.2
YearPublicationVenuePosition
2013 Soft wearable motion sensing suit for lower limb biomechanics measurements
abstract
Motion sensing has played an important role in the study of human biomechanics as well as the entertainment industry. Although existing technologies, such as optical or inertial based motion capture systems, have relatively high accuracy in detecting body motions, they still have inherent limitations with regards to mobility and wearability. In this paper, we present a soft motion sensing suit for measuring lower extremity joint motion. The sensing suit prototype includes a pair of elastic tights and three hyperelastic strain sensors. The strain sensors are made of silicone elastomer with embedded microchannels filled with conductive liquid. To form a sensing suit, these sensors are attached at the hip, knee, and ankle areas to measure the joint angles in the sagittal plane. The prototype motion sensing suit has significant potential as an autonomous system that can be worn by individuals during many activities outside the laboratory, from running to rock climbing. In this study we characterize the hyperelastic sensors in isolation to determine their mechanical and electrical responses to strain, and then demonstrate the sensing capability of the integrated suit in comparison with a ground truth optical motion capture system. Using simple calibration techniques, we can accurately track joint angles and gait phase. Our efforts result in a calculated trade off: with a maximum error less than 8%, the sensing suit does not track joints as accurately as optical motion capture, but its wearability means that it is not constrained to use only in a lab.
Yigit Mengüç, Yong-Lae Park, Ernesto Martinez-Villalpando, Patrick M. Aubin, Miriam Zisook, Leia A. Stirling 0001, Robert J. Wood, Conor J. Walsh
ICRA5