Saeid Sanei - Body Sensor Networking, Design and Algorithms

Table 3.1 Biosensors, their principle, applications, and bibliography.

Table 3.2 Use of biosensors in disease diagnosis.

1 1 Chen, S., Lach, J., Lo, B., and Yang, G.-Z. (2016). Toward pervasive gait analysis with wearable sensors: a systematic review. IEEE Journal of Biomedical and Health Informatics 20 (6): 1251–1537.

2 2 Lee, T.K.M., Belkhatir, M., and Sanei, S. (2014). A comprehensive review of past and present vision-based techniques for gait recognition. Multimedia Tools and Applications 72 (3): 2833–2869.

3 3 Lee, T.K.M., Sanei, S., and Belkhatir, M. (2011). Combining biometrics derived from different classes of nonlinear analyses of fronto-normal gait signals. IARIA International Journal of Advances on Networks and Services 4 (1–2): 232–243.

4 4 Lee, T.K.M., Belkhatir, M., Lee, P.A., and Sanei, S. (2008). Nonlinear characterisation of fronto-normal gait for human recognition. In: Advances in Multimedia Information Processing – PCM 2008, Lecture Notes in Computer Science (eds. Y.-M.R. Huang et al.), 466–475. Berlin: Springer-Verlag.

5 5 Elbaz, A., Mor, A., Segal, G. et al. (2016). Lower extremity kinematic profile of gait of patients after ankle fracture: a case-control study. Journal of Foot and Ankle Surgery 55 (5): 918–921.

6 6 Ihlen, E.A., Weiss, A., Beck, Y. et al. (2016). A comparison study of local dynamic stability measures of daily life walking in older adult community-dwelling fallers and non-fallers. Journal of Biomechanics 49 (9): 1498–1503.

7 7 Tadano, S., Takeda, R., Sasaki, K. et al. (2016). Gait characterization for osteoarthritis patients using wearable gait sensors (H-Gait systems). Journal of Biomechanics 49 (5): 684–690.

8 8 Chini, G., Ranavolo, A., Draicchio, F. et al. (2017). Local stability of the trunk in patients with degenerative cerebellar ataxia during walking. Cerebellum 16 (1): 26–33.

9 9 Gong, J., Lach, J., Qi, Y., and Goldman, M.D. (2015). Causal analysis of inertial body sensors for enhancing gait assessment separability towards multiple sclerosis diagnosis. In: Proceedings of the 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks, 1–6. IEEE.

10 10 Rapp, W., Brauner, T., Weber, L. et al. (2015). Improvement of walking speed and gait symmetry in older patients after hip arthroplasty: a prospective cohort study. BMC Musculoskeletal Disorders 16 (1): 291–298.

11 11 Rampp, A., Barth, J., Schülein, S. et al. (2015). Inertial sensor-based stride parameter calculation from gait sequences in geriatric patients. IEEE Transactions on Biomedical Engineering 62 (4): 1089–1097.

12 12 Kwasnicki, R.M., Hettiaratchy, S., Jarchi, D. et al. (2015). Assessing functional mobility after lower limb reconstruction: a psychometric evaluation of a sensor-based mobility score. Annals of Surgery 261 (4): 800–806.

13 13 Pasluosta, C.F., Barth, J., Gassner, H. et al. (2015). Pull test estimation in Parkinson's disease patients using wearable sensor technology. In: 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 3109–3112. IEEE.

14 14 Mariani, B., Jimenez, M.C., Vingerhoets, F.J., and Aminian, K. (2013). Onshoe wearable sensors for gait and turning assessment of patients with Parkinson's disease. IEEE Transactions on Biomedical Engineering 60 (1): 155–158.

15 15 Bagala, F., Klenk, J., Cappello, A. et al. (2013). Quantitative description of the lie-to-sit-to-stand-to-walk transfer by a single body-fixed sensor. IEEE Transactions on Neural Systems and Rehabilitation Engineering 21 (4): 624–633.

16 16 Barth, J., Sünkel, M., Bergner, K. et al. (2012). Combined analysis of sensor data from hand and gait motor function improves automatic recognition of Parkinson's disease. In: 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 5122–5125. IEEE.

17 17 Benson, L.C., Clermont, C.A., Watari, R. et al. (2019). Automated accelerometer-based gait event detection during multiple running conditions. Sensors (Basel) 19 (7): 1–19.

18 18 Li, R.T., Kling, S.R., Salata, M.J. et al. (2016). Wearable performance devices in sports medicine. Sports Health 8 (1): 74–78.

19 19 Simon, S.R. (2004). Quantification of human motion: gait analysis-benefits and limitations to its application to clinical problems. Journal of Biomechanics 37 (12): 1869–1880.

20 20 Jarchi, D., Pope, J., Lee, T.K.M. et al. (2018). A review on accelerometry based gait analysis and emerging clinical applications. IEEE Reviews in Biomedical Engineering 11: 177–194.