## 1 Introduction  
Cerebral strokes are the main cause of neurological impairments worldwide [1], with a survival rate of 60-75%. About 80-90% of the survivors suffer from a reduction or complete loss of their psycho-motor functions [2]. Other factors such as accidents or different diseases also affect these functions. The mobility effect negatively impacts life quality and Daily Living Activities (DLA) such as eating, grooming or dressing. There is a great necessity of rehabilitation for these patients but most classical methods are difficult to implement, because they demand a high physical effort from the therapist [3]. Robotic systems are a good option since they support the high intensity, steady performance and long activity periods required [4]. The wrist is one of the most exposed joints to trauma, injuries or strokes, and diverse devices have been developed for its rehabilitation. An exoskeleton with elastic actuators was developed in [5]. In [6], a rehabilitation system with force sensing was built. A structure for the 3-DOF movements of the wrist by either arm was presented in [7]. In [8], a training glove with pneumatic actuators is designed, and in [9] a 3-DOF exoskeleton is presented. However, none of the aforementioned works includes the detailed design of the structural component. Most developments are focused on the system control, and generally the devices are over-dimensioned and difficult to produce. The development of computing tools has accelerated the design process, simplifying the manufacture and control while ensuring a safer operation. Few works consider these aspects, highlighting the development of [PERSON] et al. [10], with a structural design carried out by metaheuristics, one element at a time. Several methodologies have been proposed, such as Concurrent Design (CD) [11], Design For Control (DFC) [12], Design For A (A = life cycle, manufacture, etc.) [13], and Multidisciplinary Design Optimization (MDO) [14]. Most structural optimization cases have both non-linear objective functions and constraints, with limited search spaces, making it impossible to solve the associated optimization problems by classic techniques, so metaheuristics are a useful tool for their solution. Many works have addressed aspects as the weight optimization to maximize stiffness [15; 16], or the topology optimization of beams for different stress types [17; 18]. Harmony Search (HS) is a metaheuristic developed by [PERSON] et al. [19] on the basis that a harmony is a certain sound combination and the search for the best harmony is analogous to finding a solution for an optimization problem [20]. It presents a good balance between exploration and exploitation, an easy and low-cost computational implementation with few mathematical requirements, and fast convergence [21]. It has been applied in fields such as engineering [22; 23; 24; 25; 26], computing [27; 28], image processing [29; 30], and electronics [31]. In relation to the scope of this work, HS has been successfully used in different medical applications. In [32], it is applied to select the adequate features for a digital hearing aid device, after classifying the acoustic environment where the user is immerse. A method called MRMR-COA-HS is proposed in [33] for a two-stage gene selection, with a hybrid combination of the Cuckoo Optimization Algorithm (COA) and HS for cancer classification. In [34], HS is used with the entropy of Kapur in a method for image segmentation by thresholding, to detect skin cancer in early stages. Another segmentation technique based on HS is presented in [35], for analyzing magnetic resonance images (MRI). In [36], the authors developed an application for medical physics, using HS to optimize the radioisotope placement of a high dose-rate brachytherapy for prostate cancer. There are also diverse works on HS-based structural design. In [37; 38], the efficiency of HS for solving this type of problems is analyzed, and a tool based on HS for the design of a three-span box-girder bridge is presented in [39].