Implementation of Bioelectrical Impedance Measuring Instrument Based on Embedded System Article Swipe
Charu Pawar
,
Munna Khan
,
J. P. Saini
,
Dev Singh
,
Manish Bhardwaj
,
Yu‐Chen Hu
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1155/2024/1024006
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1155/2024/1024006
The present research aims to measure the segmental bioelectrical impedance (BI) of the human body at multifrequency, using a server user interface-based prototype, which provides subjects with measured data online anywhere accessed by their unique identifications. The present research measures the BI of the human leg and arm at a multifrequency range of 50–400 kHz with a developed and standard device. Recorded data can be transferred to the subject using Wi-Fi technology with their unique identifications and password. The system uses Wi-Fi interfacing for real-time data measurement and online data storage. The prototype can be used commercially. The compact size of the prototype becomes the demand of the common population. The pocket carry size makes it easy to carry anywhere for regular monitoring of the human body to prevent critical disease. The resultant data show that the mean and standard deviation of the left and right leg are 282.2 ± 14.29 and 274.80 ± 13.91 Ω, respectively. Similarly, in the case of the left arm and right arm, the mean and standard deviation are 325.41 ± 16.54 and 320.73 ± 16.07 Ω, respectively. The relative error between developed and standard devices is 3.53%. Results show that the left leg and arm impedance is always greater. However, the right leg and arm muscles are stronger than the left one, with less impedance at all frequencies.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1155/2024/1024006
- https://downloads.hindawi.com/journals/mpe/2024/1024006.pdf
- OA Status
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- References
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All OpenAlex metadata
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https://doi.org/10.1155/2024/1024006Digital Object Identifier
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Implementation of Bioelectrical Impedance Measuring Instrument Based on Embedded SystemWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-04-25Full publication date if available
- Authors
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Charu Pawar, Munna Khan, J. P. Saini, Dev Singh, Manish Bhardwaj, Yu‐Chen HuList of authors in order
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https://doi.org/10.1155/2024/1024006Publisher landing page
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https://downloads.hindawi.com/journals/mpe/2024/1024006.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://downloads.hindawi.com/journals/mpe/2024/1024006.pdfDirect OA link when available
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Bioelectrical impedance analysis, Electrical impedance, Computer science, Focused Impedance Measurement, Biomedical engineering, Engineering, Electrical engineering, Medicine, Body mass index, PathologyTop concepts (fields/topics) attached by OpenAlex
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1Total citation count in OpenAlex
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2024: 1Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.aims | 3 |
| abstract_inverted_index.arm, | 167 |
| abstract_inverted_index.body | 14, 126 |
| abstract_inverted_index.case | 160 |
| abstract_inverted_index.data | 28, 62, 85, 89, 133 |
| abstract_inverted_index.easy | 116 |
| abstract_inverted_index.left | 143, 163, 197, 216 |
| abstract_inverted_index.less | 219 |
| abstract_inverted_index.mean | 137, 169 |
| abstract_inverted_index.one, | 217 |
| abstract_inverted_index.show | 134, 194 |
| abstract_inverted_index.size | 99, 113 |
| abstract_inverted_index.than | 214 |
| abstract_inverted_index.that | 135, 195 |
| abstract_inverted_index.used | 95 |
| abstract_inverted_index.user | 20 |
| abstract_inverted_index.uses | 80 |
| abstract_inverted_index.with | 26, 55, 72, 218 |
| abstract_inverted_index.13.91 | 154 |
| abstract_inverted_index.14.29 | 150 |
| abstract_inverted_index.16.07 | 180 |
| abstract_inverted_index.16.54 | 176 |
| abstract_inverted_index.282.2 | 148 |
| abstract_inverted_index.Wi-Fi | 70, 81 |
| abstract_inverted_index.carry | 112, 118 |
| abstract_inverted_index.error | 185 |
| abstract_inverted_index.human | 13, 44, 125 |
| abstract_inverted_index.makes | 114 |
| abstract_inverted_index.range | 51 |
| abstract_inverted_index.right | 145, 166, 207 |
| abstract_inverted_index.their | 33, 73 |
| abstract_inverted_index.using | 17, 69 |
| abstract_inverted_index.which | 23 |
| abstract_inverted_index.274.80 | 152 |
| abstract_inverted_index.3.53%. | 192 |
| abstract_inverted_index.320.73 | 178 |
| abstract_inverted_index.325.41 | 174 |
| abstract_inverted_index.always | 203 |
| abstract_inverted_index.common | 108 |
| abstract_inverted_index.demand | 105 |
| abstract_inverted_index.online | 29, 88 |
| abstract_inverted_index.pocket | 111 |
| abstract_inverted_index.server | 19 |
| abstract_inverted_index.system | 79 |
| abstract_inverted_index.unique | 34, 74 |
| abstract_inverted_index.Results | 193 |
| abstract_inverted_index.becomes | 103 |
| abstract_inverted_index.between | 186 |
| abstract_inverted_index.compact | 98 |
| abstract_inverted_index.device. | 60 |
| abstract_inverted_index.devices | 190 |
| abstract_inverted_index.measure | 5 |
| abstract_inverted_index.muscles | 211 |
| abstract_inverted_index.present | 1, 37 |
| abstract_inverted_index.prevent | 128 |
| abstract_inverted_index.regular | 121 |
| abstract_inverted_index.subject | 68 |
| abstract_inverted_index.50–400 | 53 |
| abstract_inverted_index.However, | 205 |
| abstract_inverted_index.Recorded | 61 |
| abstract_inverted_index.accessed | 31 |
| abstract_inverted_index.anywhere | 30, 119 |
| abstract_inverted_index.critical | 129 |
| abstract_inverted_index.disease. | 130 |
| abstract_inverted_index.greater. | 204 |
| abstract_inverted_index.measured | 27 |
| abstract_inverted_index.measures | 39 |
| abstract_inverted_index.provides | 24 |
| abstract_inverted_index.relative | 184 |
| abstract_inverted_index.research | 2, 38 |
| abstract_inverted_index.standard | 59, 139, 171, 189 |
| abstract_inverted_index.storage. | 90 |
| abstract_inverted_index.stronger | 213 |
| abstract_inverted_index.subjects | 25 |
| abstract_inverted_index.developed | 57, 187 |
| abstract_inverted_index.deviation | 140, 172 |
| abstract_inverted_index.impedance | 9, 201, 220 |
| abstract_inverted_index.password. | 77 |
| abstract_inverted_index.prototype | 92, 102 |
| abstract_inverted_index.real-time | 84 |
| abstract_inverted_index.resultant | 132 |
| abstract_inverted_index.segmental | 7 |
| abstract_inverted_index.Similarly, | 157 |
| abstract_inverted_index.monitoring | 122 |
| abstract_inverted_index.prototype, | 22 |
| abstract_inverted_index.technology | 71 |
| abstract_inverted_index.interfacing | 82 |
| abstract_inverted_index.measurement | 86 |
| abstract_inverted_index.population. | 109 |
| abstract_inverted_index.transferred | 65 |
| abstract_inverted_index.frequencies. | 223 |
| abstract_inverted_index.bioelectrical | 8 |
| abstract_inverted_index.commercially. | 96 |
| abstract_inverted_index.respectively. | 156, 182 |
| abstract_inverted_index.multifrequency | 50 |
| abstract_inverted_index.identifications | 75 |
| abstract_inverted_index.interface-based | 21 |
| abstract_inverted_index.multifrequency, | 16 |
| abstract_inverted_index.identifications. | 35 |
| cited_by_percentile_year.max | 94 |
| cited_by_percentile_year.min | 90 |
| corresponding_author_ids | https://openalex.org/A5074544822 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 6 |
| corresponding_institution_ids | https://openalex.org/I169090423 |
| citation_normalized_percentile.value | 0.61125985 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |