You will be shown an abstract from a biomedical research paper. Given this abstract, your task is to extract all unique entities of the following types: ["HealthCareActivity", "InjuryOrPoisoning", "BodySubstance", "IntellectualProduct", "AnatomicalStructure", "SpatialConcept", "Chemical", "Bacterium", "MedicalDevice", "Organization", "BiomedicalOccupationOrDiscipline", "Finding", "BiologicFunction", "Virus", "ResearchActivity", "ClinicalAttribute", "PopulationGroup", "Eukaryote", "BodySystem", "Food", "ProfessionalOrOccupationalGroup"].

Please return the output as a JSON object of the format: {"Virus": ["HIV", ...], "Bacterium": ["MRSA", ...], "AnatomicalStructure": ["Lung", ...], "BodySystem": ["CNS", ...], "BodySubstance": ["Serum", ...], "Finding": ["Headache", ...], "InjuryOrPoisoning": ["Fracture", ...], "BiologicFunction": ["Death", ...], "HealthCareActivity": ["Biopsy", ...], "ResearchActivity": ["Clinical trial", ...], "MedicalDevice": ["Lenses", ...], "SpatialConcept": ["Camps", ...], "BiomedicalOccupationOrDiscipline": ["Forensic medicine", ...], "Organization": ["WHO", ...], "ProfessionalOrOccupationalGroup": ["Provider", ...], "PopulationGroup": ["Swimmers", ...], "Chemical": ["Gold", ...], "Food": ["Rice", ...], "IntellectualProduct": ["RPAM", ...], "ClinicalAttribute": ["Biomarker", ...], "Eukaryote": ["Dogs", ...]}. The keys should be entity types and values should be lists of extracted entities belonging to the corresponding type. If you cannot find entities belonging to a specific type, the value should be [].

Only output the JSON object and do not include any additional text.

Abstract:

Mechanisms of compensation in the gait of patients with drop foot Drop foot is a complex syndrome, with multiple interactions between joints and muscles. Abnormalities in movement patterns can be measured using motion capture techniques, but identifying compensation mechanisms remains challenging. In order to identify compensatory mechanisms in patients with drop foot, this study evaluated a sample of 15 such patients using a computerized gait analysis system, as compared to a group of 15 healthy subjects. Four classes of parameters were distinguished, falling in differing intervals of percentage differences between the groups in the study. The first class comprised two kinematic parameters for which the values of percentage differences in the control group were more than 100% greater than for the patient group. The second class comprised two kinetic parameters falling in the interval of 100-49%. In the third class, in the 49-20% interval the main differences were observed for spatiotemporal parameters, whereas in the 20-4% interval the differences were distributed similarly for kinematic, kinetic and spatiotemporal parameters. These differences in gait pattern between the groups may be related to both primary motor deficits and secondary compensatory mechanisms. Generally, we conclude that drop foot affects the patients ' overall kinematic and kinetic gait parameters, with compensation seen as a chain originating from a change of movement within the ankle joint.
{"AnatomicalStructure": ["muscles"], "Bacterium": [], "BiologicFunction": ["syndrome", "movement", "drop foot", "Drop foot"], "BiomedicalOccupationOrDiscipline": ["kinematic", "kinematic parameters"], "BodySubstance": [], "BodySystem": [], "Chemical": [], "ClinicalAttribute": [], "Eukaryote": [], "Finding": ["Abnormalities", "falling", "gait", "motor deficits", "gait pattern", "movement patterns"], "Food": [], "HealthCareActivity": ["motion capture techniques", "compensation"], "InjuryOrPoisoning": [], "IntellectualProduct": [], "MedicalDevice": ["gait analysis system"], "Organization": [], "PopulationGroup": ["healthy subjects", "groups"], "ProfessionalOrOccupationalGroup": [], "ResearchActivity": ["study", "spatiotemporal parameters"], "SpatialConcept": ["ankle joint", "joints"], "Virus": []}