Maria Lindén

About Maria Lindén

Maria Lindén, With an exceptional h-index of 27 and a recent h-index of 22 (since 2020), a distinguished researcher at Mälardalens högskola, specializes in the field of Biomedical Engineering, Health technology, Sensor system, Signal processing.

His recent articles reflect a diverse array of research interests and contributions to the field:

Unobtrusive Cognitive Assessment in Smart-Homes: Leveraging Visual Encoding and Synthetic Movement Traces Data Mining

Machine learning-based classification of hypertension using CnD features from acceleration photoplethysmography and clinical parameters

PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points

State of the art of non-invasive technologies for bladder monitoring: a scoping review

A novel fiducial point extraction algorithm to detect C and D points from the acceleration photoplethysmogram (CnD)

Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring

An approach to a novel device agnostic model illustrating the relative change in physical behavior over time to support behavioral change

Automatic lesion segmentation using atrous convolutional deep neural networks in dermoscopic skin cancer images

Maria Lindén Information

University

Position

Professor in Health technology

Citations(all)

2622

Citations(since 2020)

1645

Cited By

1543

hIndex(all)

27

hIndex(since 2020)

22

i10Index(all)

66

i10Index(since 2020)

41

Email

University Profile Page

Google Scholar

Maria Lindén Skills & Research Interests

Biomedical Engineering

Health technology

Sensor system

Signal processing

Top articles of Maria Lindén

Unobtrusive Cognitive Assessment in Smart-Homes: Leveraging Visual Encoding and Synthetic Movement Traces Data Mining

Sensors

2024/2/21

Machine learning-based classification of hypertension using CnD features from acceleration photoplethysmography and clinical parameters

2023/6/22

PPGFeat: a novel MATLAB toolbox for extracting PPG fiducial points

Frontiers in Bioengineering and Biotechnology

2023/6/9

State of the art of non-invasive technologies for bladder monitoring: a scoping review

2023/3/2

A novel fiducial point extraction algorithm to detect C and D points from the acceleration photoplethysmogram (CnD)

Electronics

2023/2/28

Impact of Activities in Daily Living on Electrical Bioimpedance Measurements for Bladder Monitoring

2023/6/22

An approach to a novel device agnostic model illustrating the relative change in physical behavior over time to support behavioral change

Journal of Technology in Behavioral Science

2022/6

Maria Lindén
Maria Lindén

H-Index: 16

Automatic lesion segmentation using atrous convolutional deep neural networks in dermoscopic skin cancer images

BMC Medical Imaging

2022/5/29

Roopak Sinha
Roopak Sinha

H-Index: 12

Maria Lindén
Maria Lindén

H-Index: 16

Melanoma classification using a novel deep convolutional neural network with dermoscopic images

Sensors

2022/2/2

Roopak Sinha
Roopak Sinha

H-Index: 12

Maria Lindén
Maria Lindén

H-Index: 16

A systematic review of wearable sensors for monitoring physical activity

2022/1/12

Annica Kristoffersson
Annica Kristoffersson

H-Index: 10

Maria Lindén
Maria Lindén

H-Index: 16

Long-term condition monitoring using wearable sensors and IoT-based applications

Electromagnetic Waves and Antennas for Biomedical Applications

2021/12/20

Continuous Blood Pressure Estimation From Non-Invasive Measurements Using Support Vector Regression

2021/11/1

Maria Lindén
Maria Lindén

H-Index: 16

State-Space versus Linear Regression Models between ECG Leads

2021/9/27

Ivan Tomasic
Ivan Tomasic

H-Index: 5

Maria Lindén
Maria Lindén

H-Index: 16

Real-time and offline evaluation of myoelectric pattern recognition for the decoding of hand movements

Sensors

2021/8/23

Max Ortiz-Catalan
Max Ortiz-Catalan

H-Index: 17

Maria Lindén
Maria Lindén

H-Index: 16

Addressing evidence in health and welfare technology interventions from different perspectives

2021/6/1

Maria Lindén
Maria Lindén

H-Index: 16

Ken Redekop
Ken Redekop

H-Index: 32

Early detection of prediabetes and T2DM using wearable sensors and internet-of-things-based monitoring applications

Applied Clinical Informatics

2021/1

Maria Lindén
Maria Lindén

H-Index: 16

Health Trend Monitoring by Embedded Sensor Systems for Health

2021

A Novel Convolutional Neural Network for Continuous Blood Pressure Estimation

2021

Maria Lindén
Maria Lindén

H-Index: 16

A comparative analysis of hybrid deep learning models for human activity recognition

Sensors

2020/10/7

Impact of subthreshold transcutaneous auricular vagus nerve stimulation on the heart rate variability and atrial arrhythmias

2020/9/28

Maria Lindén
Maria Lindén

H-Index: 16

See List of Professors in Maria Lindén University(Mälardalens högskola)

Co-Authors

academic-engine