# Portable RGB-D Camera-Based System for Assessing Gait Impairment Progression in ATTRv Amyloidosis
## 1 Introduction
Recently, [PERSON] et al., in a study with 20 ATTRv amyloidosis patients (aged 49 to 78), described the ability to use the 6-Minute Walk Test (6 MWT) as a tool to monitor ATTRv amyloidosis patients, as it showed a good correlation with FAP and PND (Polyneropathy Disability) scores [22]. Nonetheless, to our knowledge, there is no study on patients' gait progression. Despite the variability of gait among subjects, there is an identifiable \"normal pattern\" [23]. Locomotion pathology produces abnormalities to this pattern, which in ATTRv amyloidosis patients was reported to be similar to the pattern of diabetic polneuropathy patients. These \"irregularities\" may be identified, at some point, by visual observation [2,24,25]. The importance of a quantitative gait analysis tool lies in the possibility of measuring and/or detecting those abnormalities as soon as possible--even before being visible to the eyes--to help improve patients' diagnosis and treatment [20]. Abnormal gait may also be studied to develop occupational therapy strategies for improving work safety and life quality, thereby extending the period of active life of patients with highly disabling diseases such as ATTRv amyloidosis. Until recently, complete full-body studies involving patients with gait impairments were only possible in dedicated laboratories, using specific and sophisticated equipment, based on multiple inertial sensors, such as accelerometers [26], or multiple infrared cameras that record the 3D movement of retro-reflective markers. The latter are placed on the patient's body using a specific configuration according to the research goal. These systems offer high precision and usability in biomechanics--often considered as the gold standard in this field--and may be combined with third-party equipment (e.g., force plates, EMG) [23,27]. However, they are usually expensive and restrictive for the majority of the population and clinical professionals. Nowadays, new methods and tools are being developed to replace complex apparatus with smaller, more portable, less expensive, and less intrusive vision-based systems that rely on RGB-D cameras. A single RGB D camera, such as the Microsoft Kinect, provides color and depth image sequences, as well as 3D body joint position data, without requiring the placement of any sensor or marker on the subject's body. Wearable sensors have also been widely used for gait analysis in different contexts [28]. However, they have the major disadvantage of having to be attached to the body, and are therefore intrusive for the patients. The use of only one or two wearable sensors can reduce their intrusiveness; however, fewer sensors can only offer limited information. To obtain full-body data, several sensors need to be attached to the different parts of the body, which can not only be complex and time-consuming to set up, but also quite uncomfortable and may restrict the movements of the patient. In this situation, markerless RGB-D cameras have the advantage of providing 3D body joint data related to the whole body in a minimally invasive way for patients, making them more suitable for use in clinical environments. Although an RGB-D camera cannot be used to continuously monitor a patient, as is possible with wearable devices, it is suitable for the scenario considered in this work, i.e., the support of clinicians during follow-up appointments with patients at the hospital.