Body Sensor Networking, Design and Algorithms. Saeid Sanei

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Body Sensor Networking, Design and Algorithms - Saeid Sanei


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using ferroceneboronic acid Robust analytical method for measuring glycated haemoglobin Wang et al. [52] 3. Uric acid biosensor Electrochemistry For detection of clinical abnormalities or diseases Erden and Kilic [53] and Kim et al. [54] 4. Acetylcholinesterase inhibition-based biosensors Electrochemistry Understanding pesticidal impact Pundir and Chauhan [55] 5. Piezoelectric biosensors Electrochemistry Detecting organophosphate and carbamate Marrazza [56] 6. Microfabricated biosensor Optical/visual biosensor using cytochrome P450 enzyme For drug development Schneider and Clark [57] 7. Hydrogel (polyacrylamide)-based biosensor Optical/visual biosensor Biomolecular immobilisation Khimji et al. [58] 8. Silicon biosensor Optical/visual/fluorescence Bioimaging, biosensing, and cancer therapy Peng et al. [59] and Shen et al. [60] 9. Quartz crystal biosensor Electromagnetic For developing ultrahigh-sensitive detection of proteins in liquids Ogi [61] 10. Nanomaterials-based biosensors Electrochemical or optical/visual/fluorescence For multifaceted applications including biomedicine, e.g. diagnostic tools Li et al. [62], Kwon and Bard [63], Zhou et al. [64], Guo [65], Hutter and Maysinger [66], Ko et al. [67], Senveli and Tigli [68], Valentini et al. [69], Lamprecht et al. [70], and Sang et al. [71] 11. Genetically encoded or fluorescence-tagged biosensor Fluorescence For understanding biological process including various molecular systems inside the cell Randriamampita and Lellouch [72], Oldach and Zhang [73], Kunzelmann et al. [74], and Wang et al. [75] 12. Microbial fuel-cell-based biosensors Optical To monitor biochemical oxygen demand and toxicity in the environment and heavy metal and pesticidal toxicity Gutierrez et al. [76] and Sun et al. [77]
No. Biosensor(s) Disease diagnosis or medical applications
1. Glucose oxidase electrode-based biosensor and HbA1c biosensor Diabetes
2. Uric acid biosensor Cardiovascular and general disease diagnosis
3. Microfabricated biosensor Optical corrections
4. Hydrogel (polyacrylamide)-based biosensor Regenerative medicine
5. Silicon biosensor Cancer biomarker development and applications
6. Nanomaterials-based biosensors For therapeutic applications

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      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


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