Jessika Jessika- Master of Science
- Master's Student at KTH Royal Institute of Technology
Jessika Jessika
- Master of Science
- Master's Student at KTH Royal Institute of Technology
Student of MSc in Nanotechnology at KTH Royal Institute of Technology
About
8
Publications
2,645
Reads
How we measure 'reads'
A 'read' is counted each time someone views a publication summary (such as the title, abstract, and list of authors), clicks on a figure, or views or downloads the full-text. Learn more
17
Citations
Introduction
Current institution
Additional affiliations
January 2020 - July 2022
Position
- Research Assistant
Description
- • Worked on a collaborative project with Faculty of Medicine of Padjadjaran University, to develop biodevice for exosome collection and analysis in cardiovascular purposes. • Collaborated with researchers from Physics Department to analyse particle properties with dynamic light scattering and isolate urinary exosome from human subjects. • Conducted experiments on flexible sensors and microfluidics fabrication, conductive inks synthesis, and nanomaterials application.
Education
August 2015 - March 2020
Publications
Publications (8)
![Fig. 1. Network architecture [6]](profile/Jessika-Jessika/publication/335795233/figure/fig1/AS:857030449451012@1581343390660/Network-architecture-6_Q320.jpg)
This paper investigates the implementation of part affinity fields in deep neural network to estimate human body pose from images and videos. The deep neural network is capable to perform human pose estimation under various body position and activities, based on human localization and human pose detection. Human localization is inferred from the pr...
In the past few years, various studies on the diagnostic medical field have been conducted which have resulted in the development of wearable devices for biomedical applications. It was concluded that POCT platform should be low-cost, easy to use, and portable. Fabric is an interesting platform for point of care testing because it has inexpensive m...
Early detection for Parkinson's Disease (PD) can be realized by investigating the speech abnormalities of the patient. Utilizing machine learning approach, PD can be well diagnosed by investigating its speech features. Oxford Parkinson's Disease (OPD) dataset, containing pieces of PD patients' speech and normal speech was used in this study. The in...
Most commercially available Surface Plasmon Resonance (SPR) devices are not equipped with convenient analysis software to be operated by the non-expert. We introduce a web-based application for SPR sample data analysis with Python’s Matplotlib and Bokeh as the primary tools. Users can directly upload and analyze the SPR data output, where the data...
The rise of wearable technology has gradually shifted modern health monitoring from clinical to personal use. Smart wearables can collect physiological signals and show them directly on a smartphone. In contemporary healthcare scenarios, this big data could aid medical doctors in online health analysis. Most currently available wearables are design...
Understanding particle size analysis is essential for pharmaceutical, mining, environmental, coatings, and other industries. Although there are numerous technologies that can be utilized to take particle size measurements, the results of those measurements are presented automatically and are sometimes difficult to understand. In this study, using t...
Diabetes mellitus is now one of the biggest health problems in the world. Based on WHO data in 2018, around 430 million world populations are diabetics and Indonesia rank sixth in the world with the most diabetic patients (10.3 million population). Quantification methods with laboratory analysis are still widely used in diagnosing types of diseases...
