No studies have analysed the acute effects of the FIFA 11+ and Harmoknee warm-up programmes on major physical performance measures. The aim of this study was to analyse the acute (post-exercise) effects of the FIFA 11+, Harmoknee and dynamic warm-up routines on several physical performance measures in amateur football players. A randomized, crossover and counterbalanced study design was used to address the purpose of this study. A total of sixteen amateur football players completed the following protocols in a randomized order on separate days: a) FIFA 11+; b) Harmoknee; and c) dynamic warm-up (DWU). In each experimental session, 19 physical performance measures (joint range of motion, hamstring to quadriceps [H/Q] strength ratios, dynamic postural control, 10 and 20 m sprint times, jump height and reactive strength index) were assessed. Measures were compared via a magnitude-based inference analysis. The results of this study showed no main effects between paired comparisons (FIFA 11+ vs. DWU, Harmoknee vs. DWU and Harmoknee vs. FIFA 11+) for joint range of motions, dynamic postural control, H/Q ratios, jumping height and reactive strength index measures. However, significant main effects (likely effects with a probability of >75–99%) were found for 10 (1.7%) and 20 (2.4%) m sprint times, demonstrating that both the FIFA 11+ and Harmoknee resulted in slower sprint times in comparison with the DWU. Therefore, neither the FIFA 11+ nor the Harmoknee routines appear to be preferable to dynamic warm-up routines currently performed by most football players prior to training sessions and matches.

Abstract.The upper limbs plays a key role in the performance of ADL, from support to total execution. However, Often rehabilitations therapies sacrifices the regaining of functionality to other functions as transportation. Therefore an automatic system capable of recognize ADL based on the information provided by upper limbs is needed. Lots of algorithms have been reported using inertial sensors with limited results. The aim of this work is to describe an algorithm to recognize some ADL performed with the upper limb, such as eating, drinking, talking by phone, combing hair and brushing teeth. The algorithm is based on an alternative novel sensor that provides information of the vertical displacement of the wrist relative to the shoulder, and can be used in a free-living environment. The detection system combines decision trees (DT) and Hidden Markov Models (HMM). Efficiencies reported goes from 61% up to 100%.

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Activities of Daily Living (ADL) have a background of selfsufficiency and survival function. Upper limbs participate actively in many ADL; particularly, activities related to feeding, communication, and grooming. The performance of such activities is a parameter of independence. Various researchers have studied ADL in a free-living environment by using inertial sensors. However, functional-activity recognition with low recognition rate is a persistent result. This work proposes the use of well-known clustering techniques for ADL recognition by using as feeding signal the vertical trajectory of wrist relative to the shoulder.

Abstract-Feeding and drinking are Activities of Daily Living which can be used to assess the motor control and functional ability of the upper limb. This paper presents the upperlimb kinematics during the execution of feeding and drinking activities, such analysis consisted in the measurement of angles of flexion for trunk and arm. Eight healthy subjects performed these activities in a simulated-environment while they were video recorded. Markers on anatomical landmarks were used to analyze the kinematics of the upper limb in the sagittal plane. Additionally an electro-hydraulic sensor was attached to each upper limb to assess the vertical position of the wrist relative to the shoulder. Results showed a difference on the angles of the elbow and trunk. The electro-hydraulic sensor showed to be an efficient way to record the vertical position of wrist.