Author:
Kumar Vaishna S.,Acharya Kavan Gangadhar,Sandeep B.,Jayavignesh T.,Chaturvedi Ashvini
Reference28 articles.
1. O’Neill T, Varlow J, Silman A, Reeve J, Reid D, Todd C, Woolf A (1994) Age and sex influences on fall characteristics. Ann Rheum Dis, 773–775
2. Kannus P, Sievanen H, Palvanen M, Jarvinen T, Parkkari J (2005) Prevention of falls and consequent injuries in elderly people. Lancet, 1885–1893
3. Holmberg AH, Johnell O, Nilsson PM, Nilsson J, Berglund G, Akesson K (2006) Risk factors for fragility fracture in middle age, a prospective population-based study of 33,000 men and women. Osteoporos, 1065–1077
4. Huynh QT, Nguyen UD, Tran SV, Nabili A, Tran BQ (2013) Fall detection system using combination accelerometer and gyroscope. In: International conference on advances in electronic devices and circuits, pp 52–56
5. Ariani A, Redmond SJ, Chang D, Lovell NH (2010) Software simulation of unobtrusive falls detection at night-time using passive infrared and pressure mat sensors. In: 32nd annual international conference of the IEEE (EMBS), pp 2115–2118
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