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Development of Smartphone-based Non-Invasive Hemoglobin Measurement
Dewantoro P.a, Gandana C.E.a, Zakaria R.O.R.H.a, Irawan Y.S.a
a Electrical Engineering Department, School of Electrical Engineering and Informatics, Institut Teknologi Bandung, Bandung, Jawa Barat, 40135, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.One of the challenges in the medical world is to transform the instrument with invasive methods into non-invasive. This is expected to reduce the risk of infection that can be caused by penetrating the tissue in the human body. Hemoglobin measurement still generally use the invasive method, ie by taking and testing blood samples from patients. Therefore, it is proposed solving this problem using PPG signals recorded from the patient’s finger using non-invasive method. The signal acquisition is done reflectively by irradiating the finger using 4 LEDs with different wavelengths and then the photodiode will capture the light that is not absorbed by the network. The hemoglobin level can be determined by calculating AC and DC components at each wavelength using linear regression method. The device will connect with smartphone using Bluetooth Low Energy 4.0 and will store the hemoglobin value that was measured. In addition, the application will show if the user is in normal condition or anemia as well as tips for people with anemia. The test results of this non-invasive device indicate 1.56 gr/dL RMS with maximum error 3.7 gr/dL and a standard deviation of 0.245 gr/dL. The results were obtained by comparing to invasive tools.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]anemia,Bluetooth low energies (BTLE),Hemoglobin levels,Linear regression methods,non-invasive,Noninvasive methods,Signal acquisitions,Standard deviation[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]anemia,bluetooth low energy,hemoglobin,non-invasive,photo plethysmography[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ISESD.2018.8605489[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]