These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

141 related articles for article (PubMed ID: 31212891)

  • 41. Prediction of activity type in preschool children using machine learning techniques.
    Hagenbuchner M; Cliff DP; Trost SG; Van Tuc N; Peoples GE
    J Sci Med Sport; 2015 Jul; 18(4):426-31. PubMed ID: 25088983
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Suitability of Smartphone Inertial Sensors for Real-Time Biofeedback Applications.
    Kos A; Tomažič S; Umek A
    Sensors (Basel); 2016 Feb; 16(3):301. PubMed ID: 26927125
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Accelerometry-based gait characteristics evaluated using a smartphone and their association with fall risk in people with chronic stroke.
    Isho T; Tashiro H; Usuda S
    J Stroke Cerebrovasc Dis; 2015 Jun; 24(6):1305-11. PubMed ID: 25881773
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Reliability and validity of a smartphone-based assessment of gait parameters across walking speed and smartphone locations: Body, bag, belt, hand, and pocket.
    Silsupadol P; Teja K; Lugade V
    Gait Posture; 2017 Oct; 58():516-522. PubMed ID: 28961548
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Smartphone Authentication System Using Personal Gaits and a Deep Learning Model.
    Choi J; Choi S; Kang T
    Sensors (Basel); 2023 Jul; 23(14):. PubMed ID: 37514689
    [TBL] [Abstract][Full Text] [Related]  

  • 46. Validity of the Apple iPhone® /iPod Touch® as an accelerometer-based physical activity monitor: a proof-of-concept study.
    Nolan M; Mitchell JR; Doyle-Baker PK
    J Phys Act Health; 2014 May; 11(4):759-69. PubMed ID: 23575387
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Recognition of Typical Locomotion Activities Based on the Sensor Data of a Smartphone in Pocket or Hand.
    Ebner M; Fetzer T; Bullmann M; Deinzer F; Grzegorzek M
    Sensors (Basel); 2020 Nov; 20(22):. PubMed ID: 33212894
    [TBL] [Abstract][Full Text] [Related]  

  • 48. LSTM-Guided Coaching Assistant for Table Tennis Practice.
    Lim SM; Oh HC; Kim J; Lee J; Park J
    Sensors (Basel); 2018 Nov; 18(12):. PubMed ID: 30477175
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Assessment of walking, running, and jumping movement features by using the inertial measurement unit.
    Lee YS; Ho CS; Shih Y; Chang SY; Róbert FJ; Shiang TY
    Gait Posture; 2015 May; 41(4):877-81. PubMed ID: 25819717
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Determination of the optimal number of linked rigid-bodies of the trunk during walking and running based on Akaike's information criterion.
    Kudo S; Fujimoto M; Sato T; Nagano A
    Gait Posture; 2020 Mar; 77():264-268. PubMed ID: 32087596
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Ablation Analysis to Select Wearable Sensors for Classifying Standing, Walking, and Running.
    Gonzalez S; Stegall P; Edwards H; Stirling L; Siu HC
    Sensors (Basel); 2020 Dec; 21(1):. PubMed ID: 33396734
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Ensem-HAR: An Ensemble Deep Learning Model for Smartphone Sensor-Based Human Activity Recognition for Measurement of Elderly Health Monitoring.
    Bhattacharya D; Sharma D; Kim W; Ijaz MF; Singh PK
    Biosensors (Basel); 2022 Jun; 12(6):. PubMed ID: 35735541
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Navigating Virtual Environments Using Leg Poses and Smartphone Sensors.
    Tsaramirsis G; Buhari SM; Basheri M; Stojmenovic M
    Sensors (Basel); 2019 Jan; 19(2):. PubMed ID: 30642131
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Using Machine Learning and Smartphone and Smartwatch Data to Detect Emotional States and Transitions: Exploratory Study.
    Sultana M; Al-Jefri M; Lee J
    JMIR Mhealth Uhealth; 2020 Sep; 8(9):e17818. PubMed ID: 32990638
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Smartphone Pedometer Sensor Application for Evaluating Disease Activity and Predicting Comorbidities in Patients with Rheumatoid Arthritis: A Validation Study.
    Wagner SR; Gregersen RR; Henriksen L; Hauge EM; Keller KK
    Sensors (Basel); 2022 Dec; 22(23):. PubMed ID: 36502098
    [TBL] [Abstract][Full Text] [Related]  

  • 56. Reliability of smartphone-based gait measurements for quantification of physical activity/inactivity levels.
    Ebara T; Azuma R; Shoji N; Matsukawa T; Yamada Y; Akiyama T; Kurihara T; Yamada S
    J Occup Health; 2017 Nov; 59(6):506-512. PubMed ID: 28835575
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Human Activity Recognition Using Inertial Sensors in a Smartphone: An Overview.
    Sousa Lima W; Souto E; El-Khatib K; Jalali R; Gama J
    Sensors (Basel); 2019 Jul; 19(14):. PubMed ID: 31330919
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Monitoring Student Activities with Smartwatches: On the Academic Performance Enhancement.
    Herrera-Alcántara O; Barrera-Animas AY; González-Mendoza M; Castro-Espinoza F
    Sensors (Basel); 2019 Apr; 19(7):. PubMed ID: 30987130
    [TBL] [Abstract][Full Text] [Related]  

  • 59. ADLAuth: Passive Authentication Based on Activity of Daily Living Using Heterogeneous Sensing in Smart Cities.
    Naseer M; Azam MA; Ul-Haq ME; Ejaz W; Khalid A
    Sensors (Basel); 2019 May; 19(11):. PubMed ID: 31146477
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Development of a method for walking step observation based on large-scale GPS data.
    Nagata S; Nakaya T; Hanibuchi T; Nakaya N; Hozawa A
    Int J Health Geogr; 2022 Sep; 21(1):10. PubMed ID: 36071501
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.