BPG is committed to discovery and dissemination of knowledge
Cited by in F6Publishing
For: Buisseret F, Catinus L, Grenard R, Jojczyk L, Fievez D, Barvaux V, Dierick F. Timed Up and Go and Six-Minute Walking Tests with Wearable Inertial Sensor: One Step Further for the Prediction of the Risk of Fall in Elderly Nursing Home People. Sensors (Basel) 2020;20:E3207. [PMID: 32516995 DOI: 10.3390/s20113207] [Cited by in Crossref: 7] [Cited by in F6Publishing: 7] [Article Influence: 3.5] [Reference Citation Analysis]
Number Citing Articles
1 Zhou Y, Zia Ur Rehman R, Hansen C, Maetzler W, Del Din S, Rochester L, Hortobágyi T, Lamoth CJC. Classification of Neurological Patients to Identify Fallers Based on Spatial-Temporal Gait Characteristics Measured by a Wearable Device. Sensors (Basel) 2020;20:E4098. [PMID: 32717848 DOI: 10.3390/s20154098] [Cited by in Crossref: 4] [Cited by in F6Publishing: 2] [Article Influence: 2.0] [Reference Citation Analysis]
2 Roshdibenam V, Jogerst GJ, Butler NR, Baek S. Machine Learning Prediction of Fall Risk in Older Adults Using Timed Up and Go Test Kinematics. Sensors (Basel) 2021;21:3481. [PMID: 34067644 DOI: 10.3390/s21103481] [Reference Citation Analysis]
3 Dierick F, Stoffel PL, Schütz G, Buisseret F. High Specificity of Single Inertial Sensor-Supplemented Timed Up and Go Test for Assessing Fall Risk in Elderly Nursing Home Residents. Sensors (Basel) 2022;22:2339. [PMID: 35336510 DOI: 10.3390/s22062339] [Reference Citation Analysis]
4 Rezola-Pardo C, Irazusta J, Mugica-Errazquin I, Gamio I, Sarquis-Adamson Y, Gil SM, Ugartemendia M, Montero-Odasso M, Rodriguez-Larrad A. Effects of multicomponent and dual-task exercise on falls in nursing homes: The AgeingOn Dual-Task study. Maturitas 2022;164:15-22. [PMID: 35763894 DOI: 10.1016/j.maturitas.2022.06.006] [Reference Citation Analysis]
5 Jeong YK, Baek KR. Asymmetric Gait Analysis Using a DTW Algorithm with Combined Gyroscope and Pressure Sensor. Sensors (Basel) 2021;21:3750. [PMID: 34071372 DOI: 10.3390/s21113750] [Reference Citation Analysis]
6 Ahmad S, Jenkins M. Artificial Intelligence for Nursing Practice and Management: Current and Potential Research and Education. Comput Inform Nurs 2022;40:139-44. [PMID: 35244030 DOI: 10.1097/CIN.0000000000000871] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
7 Bezold J, Krell-Roesch J, Eckert T, Jekauc D, Woll A. Sensor-based fall risk assessment in older adults with or without cognitive impairment: a systematic review. Eur Rev Aging Phys Act 2021;18:15. [PMID: 34243722 DOI: 10.1186/s11556-021-00266-w] [Reference Citation Analysis]
8 Choi J, Parker SM, Knarr BA, Gwon Y, Youn JH. Wearable Sensor-Based Prediction Model of Timed up and Go Test in Older Adults. Sensors (Basel) 2021;21:6831. [PMID: 34696041 DOI: 10.3390/s21206831] [Reference Citation Analysis]
9 Douthit BJ, Walden RL, Cato K, Coviak CP, Cruz C, D'Agostino F, Forbes T, Gao G, Kapetanovic TA, Lee MA, Pruinelli L, Schultz MA, Wieben A, Jeffery AD. Data Science Trends Relevant to Nursing Practice: A Rapid Review of the 2020 Literature. Appl Clin Inform 2022;13:161-79. [PMID: 35139564 DOI: 10.1055/s-0041-1742218] [Reference Citation Analysis]
10 Vasquez BA, Betriana F, Nemenzo E, Inabangan AK, Tanioka R, Garcia L, Juntasopeepun P, Tanioka T, Locsin RC. Effects of Healthcare Technologies on the Promotion of Physical Activities in Older Persons: A Systematic Review. Inform Health Soc Care 2022;:1-15. [PMID: 35699246 DOI: 10.1080/17538157.2022.2086874] [Reference Citation Analysis]
11 Tateno S, Meng F, Qian R, Hachiya Y. Privacy-Preserved Fall Detection Method with Three-Dimensional Convolutional Neural Network Using Low-Resolution Infrared Array Sensor. Sensors (Basel) 2020;20:E5957. [PMID: 33096820 DOI: 10.3390/s20205957] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
12 Ko JB, Kim KB, Shin YS, Han H, Han SK, Jung DY, Hong JS. Predicting Sarcopenia of Female Elderly from Physical Activity Performance Measurement Using Machine Learning Classifiers. Clin Interv Aging 2021;16:1723-33. [PMID: 34611396 DOI: 10.2147/CIA.S323761] [Reference Citation Analysis]
13 Ferreira RN, Ribeiro NF, Santos CP. Fall Risk Assessment Using Wearable Sensors: A Narrative Review. Sensors (Basel) 2022;22:984. [PMID: 35161731 DOI: 10.3390/s22030984] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
14 Hsu YC, Wang H, Zhao Y, Chen F, Tsui KL. Automatic Recognition and Analysis of Balance Activity in Community-Dwelling Older Adults: Algorithm Validation. J Med Internet Res 2021;23:e30135. [PMID: 34932008 DOI: 10.2196/30135] [Reference Citation Analysis]