Implementing an intuitive control law for an upper-limb exoskeleton dedicated to force augmentation is a challenging issue in the field of human-robot collaboration. The aim of this study is to design an innovative approach to assist carrying an unknown load without using force sensors or specific handle. The method is based on user's intentions estimated through a wireless EMG armband allowing movement direction and intensity estimation along 1 Degree of Freedom. This control law aimed to behave like a gravity compensation except that the mass of the load does not need to be known. The proposed approach was tested on 10 participants during a lifting task with a single Degree of Freedom upper-limb exoskeleton. Participants performed it in three different conditions : without assistance, with an exact gravity compensation and with the proposed method based on EMG armband. The evaluation of the efficiency of the assistance was based on EMG signals captured on seven muscles (objective indicator) and a questionnaire (subjective indicator). Results showed a statically significant reduction of mean activity of the biceps, erector spinae and deltoid by 20%±14%, 18%±12% and 25% ± 16% respectively while comparing the proposed method with no assistance. In addition, similar muscle activities were found both in the proposed method and the traditional gravity compensation. Subjective evaluation showed better precision, efficiency and responsiveness of the proposed method compared to the traditional one.

Apathy is a neurological symptom common to several brain diseases (e.g., behavioral variant of fronto-temporal dementia, bvFTD). It can be defined as a quantitative reduction of voluntary or goal-directed behavior. ECOCAPTURE is a method developed to assess apathy in a quantitative and objective way. It consists in the observation of patient's behavior in a multi-step scenario reproducing a brief, real-life situation. It is performed in a functional exploration platform transformed into a waiting room equipped with video and sensor-based data acquisition system. The use of 3D accelerometer is well-established to assess subject's movement during activities (i.e. actigraphy). We described the method and the preliminary results in patients (n=12) with bvFTD matched to healthy participants (n=11). This actigraphy study aims to retain some metrics leading to a differentiation between patients and control subjects.