Maria Lindén
Maria Lindén
Professor in Health technology, Mälardalen University
Verified email at
Cited by
Cited by
A systematic review of wearable patient monitoring systems–current challenges and opportunities for clinical adoption
MM Baig, H GholamHosseini, AA Moqeem, F Mirza, M Lindén
Journal of medical systems 41, 1-9, 2017
Electrical characteristics of conductive yarns and textile electrodes for medical applications
L Rattfält, M Lindén, P Hult, L Berglin, P Ask
Medical & Biological Engineering & Computing 45, 1251-1257, 2007
A deep machine learning method for classifying cyclic time series of biological signals using time-growing neural network
A Gharehbaghi, M Lindén
IEEE transactions on neural networks and learning systems 29 (9), 4102-4115, 2017
Challenges and issues in multisensor fusion approach for fall detection
G Koshmak, A Loutfi, M Linden
Journal of Sensors 2016, 2016
Blood flow measurements at different depths using photoplethysmography and laser Doppler techniques
S Bergstrand, LG Lindberg, AC Ek, M Lindén, M Lindgren
Skin research and technology 15 (2), 139-147, 2009
Melanoma classification using a novel deep convolutional neural network with dermoscopic images
R Kaur, H GholamHosseini, R Sinha, M Lindén
Sensors 22 (3), 1134, 2022
Evaluation of surface EMG-based recognition algorithms for decoding hand movements
S Abbaspour, M Lindén, H Gholamhosseini, A Naber, M Ortiz-Catalan
Medical & biological engineering & computing 58, 83-100, 2020
A technique based on laser Doppler flowmetry and photoplethysmography for simultaneously monitoring blood flow at different tissue depths
J Hagblad, LG Lindberg, A Kaisdotter Andersson, S Bergstrand, ...
Medical & biological engineering & computing 48, 415-422, 2010
Evaluation of the android-based fall detection system with physiological data monitoring
GA Koshmak, M Linden, A Loutfi
2013 35th Annual International Conference of the IEEE Engineering in …, 2013
A comparative analysis of hybrid deep learning models for human activity recognition
S Abbaspour, F Fotouhi, A Sedaghatbaf, H Fotouhi, M Vahabi, M Linden
Sensors 20 (19), 5707, 2020
An overview on the internet of things for health monitoring systems
MU Ahmed, M Björkman, A Čaušević, H Fotouhi, M Lindén
Internet of Things. IoT Infrastructures: Second International Summit, IoT …, 2016
Laser-Doppler perfusion imaging of microvascular blood flow in rabbit tenuissimus muscle
M Linden, A Sirsjo, L Lindbom, G Nilsson, A Gidlof
American Journal of Physiology-Heart and Circulatory Physiology 269 (4 …, 1995
A systematic review on the use of wearable body sensors for health monitoring: a qualitative synthesis
A Kristoffersson, M Lindén
Sensors 20 (5), 1502, 2020
Evaluation of antidecubitus mattresses
A Jonsson, M Lindén, M Lindgren, LÅ Malmqvist, Y Bäcklund
Medical and Biological Engineering and Computing 43, 541-547, 2005
Thrombolytic therapy
MU Baig, J Bodle
StatPearls [Internet], 2022
A novel approach for removing ECG interferences from surface EMG signals using a combined ANFIS and wavelet
S Abbaspour, A Fallah, M Lindén, H Gholamhosseini
Journal of Electromyography and Kinesiology 26, 52-59, 2016
Signal quality improvement algorithms for MEMS gyroscope-based human motion analysis systems: A systematic review
J Du, C Gerdtman, M Lindén
Sensors 18 (4), 1123, 2018
Machine learning-based clinical decision support system for early diagnosis from real-time physiological data
MM Baig, HG Hosseini, M Lindén
2016 IEEE region 10 conference (TENCON), 2943-2946, 2016
Evaluation of wavelet based methods in removing motion artifact from ECG signal
S Abbaspour, H Gholamhosseini, M Linden
16th Nordic-Baltic Conference on Biomedical Engineering: 16. NBC & 10. MTD …, 2015
A systematic review of wearable sensors for monitoring physical activity
A Kristoffersson, M Lindén
Sensors 22 (2), 573, 2022
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