Wearable Movement Exploration Device with Machine Learning Algorithm for Screening and Tracking Diabetic Neuropathy-A Cross-Sectional, Diagnostic, Comparative Study.

BACKGROUND: Diabetic neuropathy is one of the most common complications of diabetes mellitus. The aim of this study is to evaluate the Moveo device, a novel device that uses a machine learning (ML) algorithm to detect and track diabetic neuropathy. The Moveo device comprises 4 sensors positioned on the back of the hands and feet accompanied by a mobile application that gathers data and ML algorithms that are hosted on a cloud platform. The sensors measure movement signals, which are then transferred to the cloud through the mobile application. The cloud triggers a pipeline for feature extraction and subsequently feeds the ML model with these extracted features. METHODS: The pilot study included 23 participants. Eleven patients with diabetes and suspected diabetic neuropathy were included in the experimental group. In the control group, 8 patients had suspected radiculopathy, and 4 participants were healthy. All participants underwent an electrodiagnostic examination (EDx) and a Moveo examination, which consists of sensors placed on the feet and back of the participant's hands and use of the mobile application. The participant performs six tests that are part of a standard neurological examination, and a ML algorithm calculates the probability of diabetic neuropathy. A user experience questionnaire was used to compare participant experiences with regard to both methods. RESULTS: The total accuracy of the algorithm is 82.1%, with 78% sensitivity and 87% specificity. A high linear correlation up to 0.722 was observed between Moveo and EDx features, which underpins the model's adequacy. The user experience questionnaire revealed that the majority of patients preferred the less painful method. CONCLUSIONS: Moveo represents an accurate, easy-to-use device suitable for home environments, showing promising results and potential for future usage.

Neurological and electroneurography findings in patients with systemic sclerosis and symptoms of neuropathic pain in extremities.

OBJECTIVE: To analyze neurological and electroneurography (ENG) findings in patients with systemic sclerosis (SSc) and symptoms of neuropathic pain in upper and lower extremities. PATIENTS AND METHODS: Using the PainDetect questionnaire, 42 consecutive patients with SSc (38 women and 4 men) were screened for the presence of neuropathic pain in upper and/or lower extremities. Patients with previously diagnosed diabetes or other metabolic diseases, malignancy, other autoimmune disorders, or any neurological or psychiatric disease, were not included. Neurological examination, ENG, and laboratory analyses (glycated hemoglobin-HbA1C, and vitamin B12) were performed in SSc patients with neuropathic pain in extremities. Methods of descriptive statistics were used to summarize the data. RESULTS: Eleven patients (26.2%) had significant symptoms of neuropathic pain in extremities. Neurological examination indicated polyneuropathy in 10/11 (90.9%) of patients. Symmetrical hyperesthesia in the lower and/or upper extremities was found in ten patients. Symmetrical hyporeflexia was found in 7/11 (63.6%) of patients in the arms, and 6/11 (54.4%) of patients in the legs. Proprioception was diminished in 3/11 (27.3%), whilst pallhypesthesia was present in all patients. However, polyneuropathy could be confirmed by ENG only in four out of ten SSc patients, who had typical neurological findings for polyneuropathy. Hypoesthesia in a specific lumbar root dermatome, suggesting radiculopathy, was found in 6/11 (54.5%) of patients. Asymmetrical hyporeflexia was noticed in 2/11 (18.1%) of patients in the lower limbs. Seven patients (63.6%) had signs of radiculopathy in at least one root dermatome on ENG. CONCLUSION: A significant number of SSc patients with neuropathic pain in the upper and/or lower extremities have symptoms and signs of polyneuropathy undetectable by ENG, which indirectly suggests the presence of small-fiber polyneuropathy in these patients. In some patients, radiculopathy cannot be excluded as possible co-morbid non-scleroderma condition associated with neuropathic pain.

Common Causes of Pain in Systemic Sclerosis: Frequency, Severity, and Relationship to Disease Status, Depression, and Quality of Life.

BACKGROUND: In routine clinical practice, healthcare professionals draw little attention to pain in patients with systemic sclerosis (SSc). Pain has adverse effects on functional ability, social and emotional wellbeing. AIMS: This study aims to assess the frequency and severity of different types of pain in patients with SSc, and the relationship of pain with disease status, depression and quality of life. DESIGN: Consecutive patients with SSc were included in this cross-sectional study. Patients with previously diagnosed painful diseases or conditions (other rheumatic diseases, angina pectoris, neurological disorders, etc.) were excluded. SETTINGS: Patients, who visited our rheumatology outpatient clinic from February to November 2016, participated in this study. PARTICIPANTS/SUBJECTS: 42 consecutive patients with SSc (38 women and 4 men), mean age 56.5 years, mean disease duration 9.5 years, were included. METHODS: All patients filled in a questionnaire, to indicate the presence or absence of some predefined pain syndromes. Disease status was assessed using the Scleroderma Assessment Questionnaire (SAQ), symptoms of depression by the Beck's Depression Inventory (BDI), whilst the quality of life was evaluated using the EuroQol questionnaire. RESULTS: It was found that 92.9% of SSc patients suffer from different types of pain, and 45.2% of patients have pain every day. Joint pain was the most common type of pain, present in 78.6% of patients, followed by pain associated with Raynaud's phenomenon (69%), back pain (47.6%), headache (31%), chest pain (23.8%), odynophagia (21.4%) and painful digital ulcers (19%). Symptoms of neuropathic pain were noticed in 26.2% of patients. Severe joint pain, everyday pain and symptoms of neuropathic pain in SSc were associated with more severe disease and poorer quality of life. Pain related to Raynaud's phenomenon, digital ulcers, odynophagia and joint pain were associated with significant symptoms of depression. CONCLUSION: The majority of patients with SSc suffer from different types of pain. Pain is associated with more severe disease, depression and poor quality of life.