Phase Optimization for Multipoint Haptic Feedback Based on Ultrasound Array Article Swipe
Zhili Long
,
Shuyuan Ye
,
Z. Ellen Peng
,
Yuyang Yuan
,
Zhouhua Li
·
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202112.0434.v1
YOU?
·
· 2021
· Open Access
·
· DOI: https://doi.org/10.20944/preprints202112.0434.v1
Ultrasound based haptic feedback is a potential technology for human-computer interaction (HCI) with the advantages of low cost, low power consumption and controlled force. In this paper, the phase optimization for multipoint haptic feedback based on ultrasound array is investigated and the corresponding experimental verification is provided. A mathematical model of acoustic pressure is established for the ultrasound array and then a phase optimization model for an ultrasound transducer is constructed. We propose a pseudo-inverse (PINV) algorithm to accurately determine the phase contribution of each transducer in the ultrasound array. By controlling the phase difference of the ultrasound array, the multipoint focusing forces are formed leading to various shapes such as geometries and letters that can be visualized. Because the unconstrained PINV solution results in unequal amplitudes for each transducer, a weighted amplitude iterative optimization is deployed to further optimize the phase solution, by which the uniform amplitude distributions of each transducer are obtained. For the purpose of experimental verifications, a platform of ultrasound haptic feedback consisting of a Field Programmable Gate Array (FPGA), an electrical circuit and an ultrasound transducer array is prototyped. The haptic performances of single point, multiple points and dynamic trajectory were verified by controlling the ultrasound force exerted on the liquid surface. The experimental results demonstrate that the proposed phase optimization model and theoretical results are effective and feasible, and the acoustic pressure distribution is consistent with the simulation results.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.20944/preprints202112.0434.v1
- https://www.preprints.org/manuscript/202112.0434/v1/download
- OA Status
- green
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4200587818
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4200587818Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.20944/preprints202112.0434.v1Digital Object Identifier
- Title
-
Phase Optimization for Multipoint Haptic Feedback Based on Ultrasound ArrayWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2021Year of publication
- Publication date
-
2021-12-27Full publication date if available
- Authors
-
Zhili Long, Shuyuan Ye, Z. Ellen Peng, Yuyang Yuan, Zhouhua LiList of authors in order
- Landing page
-
https://doi.org/10.20944/preprints202112.0434.v1Publisher landing page
- PDF URL
-
https://www.preprints.org/manuscript/202112.0434/v1/downloadDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.preprints.org/manuscript/202112.0434/v1/downloadDirect OA link when available
- Concepts
-
Transducer, Haptic technology, Computer science, Ultrasound, Amplitude, Phase (matter), Acoustics, Ultrasonic sensor, Simulation, Physics, Optics, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
-
30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Gate | 171 |
| abstract_inverted_index.PINV | 121 |
| abstract_inverted_index.each | 84, 128, 150 |
| abstract_inverted_index.such | 109 |
| abstract_inverted_index.that | 114, 211 |
| abstract_inverted_index.then | 60 |
| abstract_inverted_index.this | 25 |
| abstract_inverted_index.were | 195 |
| abstract_inverted_index.with | 12, 231 |
| abstract_inverted_index.(HCI) | 11 |
| abstract_inverted_index.Array | 172 |
| abstract_inverted_index.Field | 169 |
| abstract_inverted_index.array | 37, 58, 181 |
| abstract_inverted_index.based | 1, 34 |
| abstract_inverted_index.cost, | 17 |
| abstract_inverted_index.force | 201 |
| abstract_inverted_index.model | 49, 64, 216 |
| abstract_inverted_index.phase | 28, 62, 81, 93, 141, 214 |
| abstract_inverted_index.power | 19 |
| abstract_inverted_index.which | 144 |
| abstract_inverted_index.(PINV) | 75 |
| abstract_inverted_index.array, | 98 |
| abstract_inverted_index.array. | 89 |
| abstract_inverted_index.force. | 23 |
| abstract_inverted_index.forces | 102 |
| abstract_inverted_index.formed | 104 |
| abstract_inverted_index.haptic | 2, 32, 164, 185 |
| abstract_inverted_index.liquid | 205 |
| abstract_inverted_index.paper, | 26 |
| abstract_inverted_index.point, | 189 |
| abstract_inverted_index.points | 191 |
| abstract_inverted_index.shapes | 108 |
| abstract_inverted_index.single | 188 |
| abstract_inverted_index.(FPGA), | 173 |
| abstract_inverted_index.Because | 118 |
| abstract_inverted_index.circuit | 176 |
| abstract_inverted_index.dynamic | 193 |
| abstract_inverted_index.exerted | 202 |
| abstract_inverted_index.further | 138 |
| abstract_inverted_index.leading | 105 |
| abstract_inverted_index.letters | 113 |
| abstract_inverted_index.propose | 72 |
| abstract_inverted_index.purpose | 156 |
| abstract_inverted_index.results | 123, 209, 219 |
| abstract_inverted_index.unequal | 125 |
| abstract_inverted_index.uniform | 146 |
| abstract_inverted_index.various | 107 |
| abstract_inverted_index.acoustic | 51, 226 |
| abstract_inverted_index.deployed | 136 |
| abstract_inverted_index.feedback | 3, 33, 165 |
| abstract_inverted_index.focusing | 101 |
| abstract_inverted_index.multiple | 190 |
| abstract_inverted_index.optimize | 139 |
| abstract_inverted_index.platform | 161 |
| abstract_inverted_index.pressure | 52, 227 |
| abstract_inverted_index.proposed | 213 |
| abstract_inverted_index.results. | 234 |
| abstract_inverted_index.solution | 122 |
| abstract_inverted_index.surface. | 206 |
| abstract_inverted_index.verified | 196 |
| abstract_inverted_index.weighted | 131 |
| abstract_inverted_index.algorithm | 76 |
| abstract_inverted_index.amplitude | 132, 147 |
| abstract_inverted_index.determine | 79 |
| abstract_inverted_index.effective | 221 |
| abstract_inverted_index.feasible, | 223 |
| abstract_inverted_index.iterative | 133 |
| abstract_inverted_index.obtained. | 153 |
| abstract_inverted_index.potential | 6 |
| abstract_inverted_index.provided. | 46 |
| abstract_inverted_index.solution, | 142 |
| abstract_inverted_index.Ultrasound | 0 |
| abstract_inverted_index.accurately | 78 |
| abstract_inverted_index.advantages | 14 |
| abstract_inverted_index.amplitudes | 126 |
| abstract_inverted_index.consistent | 230 |
| abstract_inverted_index.consisting | 166 |
| abstract_inverted_index.controlled | 22 |
| abstract_inverted_index.difference | 94 |
| abstract_inverted_index.electrical | 175 |
| abstract_inverted_index.geometries | 111 |
| abstract_inverted_index.multipoint | 31, 100 |
| abstract_inverted_index.simulation | 233 |
| abstract_inverted_index.technology | 7 |
| abstract_inverted_index.trajectory | 194 |
| abstract_inverted_index.transducer | 68, 85, 151, 180 |
| abstract_inverted_index.ultrasound | 36, 57, 67, 88, 97, 163, 179, 200 |
| abstract_inverted_index.consumption | 20 |
| abstract_inverted_index.controlling | 91, 198 |
| abstract_inverted_index.demonstrate | 210 |
| abstract_inverted_index.established | 54 |
| abstract_inverted_index.interaction | 10 |
| abstract_inverted_index.prototyped. | 183 |
| abstract_inverted_index.theoretical | 218 |
| abstract_inverted_index.transducer, | 129 |
| abstract_inverted_index.visualized. | 117 |
| abstract_inverted_index.Programmable | 170 |
| abstract_inverted_index.constructed. | 70 |
| abstract_inverted_index.contribution | 82 |
| abstract_inverted_index.distribution | 228 |
| abstract_inverted_index.experimental | 43, 158, 208 |
| abstract_inverted_index.investigated | 39 |
| abstract_inverted_index.mathematical | 48 |
| abstract_inverted_index.optimization | 29, 63, 134, 215 |
| abstract_inverted_index.performances | 186 |
| abstract_inverted_index.verification | 44 |
| abstract_inverted_index.corresponding | 42 |
| abstract_inverted_index.distributions | 148 |
| abstract_inverted_index.unconstrained | 120 |
| abstract_inverted_index.human-computer | 9 |
| abstract_inverted_index.pseudo-inverse | 74 |
| abstract_inverted_index.verifications, | 159 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/7 |
| sustainable_development_goals[0].score | 0.8500000238418579 |
| sustainable_development_goals[0].display_name | Affordable and clean energy |
| citation_normalized_percentile.value | 0.19510598 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |