Real-time crop row detection using computer vision- application in agricultural robots.

The goal of achieving autonomous navigation for agricultural robots poses significant challenges, mostly arising from the substantial natural variations in crop row images as a result of weather conditions and the growth stages of crops. The processing of the detection algorithm also must be significantly low for real-time applications. In order to address the aforementioned requirements, we propose a crop row detection algorithm that has the following features: Firstly, a projective transformation is applied to transform the camera view and a color-based segmentation is employed to distinguish crop and weed from the background.

A Handheld Quantifiable Soft Tissue Manipulation Device for Tracking Real-Time Dispersive Force-Motion Patterns to Characterize Manual Therapy Treatment.

Objective: Low back pain (LBP) is one of the leading neuromusculoskeletal (NMSK) problems around the globe. Soft Tissue Manipulation (STM) is a force-based, non-invasive intervention used to clinically address NMSK pain conditions. Current STM practice standards are mostly subjective, suggesting an urgent need for quantitative metrics.

Quantifiable Soft Tissue Manipulation (QSTM™) - A novel modality to improve clinical manual therapy with objective metrics.

Soft Tissue Manipulation (STM), a form of mechanotherapy, offers a clinical modality to examine and treat Neuromusculoskeletal (NMS) pain disorders and dysfunction. The, current STM practice is mostly subjective and reliant on anecdotal patient feedback and lacks quantification with objective metrics. This paper proposes Quantifiable Soft Tissue Manipulation (QSTM™), a sensor based computerized technological advancement in Soft tissue examination and treatment enabling new standard of practice in manual therapy.

Improving the Robustness of Object Detection Through a Multi-Camera-Based Fusion Algorithm Using Fuzzy Logic.

A single camera creates a bounding box (BB) for the detected object with certain accuracy through a convolutional neural network (CNN). However, a single RGB camera may not be able to capture the actual object within the BB even if the CNN detector accuracy is high for the object. In this research, we present a solution to this limitation through the usage of multiple cameras, projective transformation, and a fuzzy logic-based fusion.

Time-Domain Data Fusion Using Weighted Evidence and Dempster-Shafer Combination Rule: Application in Object Classification.

To apply data fusion in time-domain based on Dempster-Shafer (DS) combination rule, an 8-step algorithm with novel entropy function is proposed. The 8-step algorithm is applied to time-domain to achieve the sequential combination of time-domain data. Simulation results showed that this method is successful in capturing the changes (dynamic behavior) in time-domain object classification.

Paradox Elimination in Dempster-Shafer Combination Rule with Novel Entropy Function: Application in Decision-Level Multi-Sensor Fusion.

Multi-sensor data fusion technology in an important tool in building decision-making applications. Modified Dempster-Shafer (DS) evidence theory can handle conflicting sensor inputs and can be applied without any prior information. As a result, DS-based information fusion is very popular in decision-making applications, but original DS theory produces counterintuitive results when combining highly conflicting evidences from multiple sensors.

Development of an Artificial Finger-Like Knee Loading Device to Promote Bone Health.

This study presents the development of an innovative artificial finger-like device that provides position specific mechanical loads at the end of the long bone and induces mechanotransduction in bone. Bone cells such as osteoblasts are the mechanosensitive cells that regulate bone remodelling. When they receive gentle, periodic mechanical loads, new bone formation is promoted.

A Mechatronic Loading Device to Stimulate Bone Growth via a Human Knee.

This paper presents the design of an innovative device that applies dynamic mechanical load to human knee joints. Dynamic loading is employed by applying cyclic and periodic force on a target area. The repeated force loading was considered to be an effective modality for repair and rehabilitation of long bones that are subject to ailments like fractures, osteoporosis, osteoarthritis, etc.

Development of a Portable Knee Rehabilitation Device That Uses Mechanical Loading.

Joint loading is a recently developed mechanical modality, which potentially provides a therapeutic regimen to activate bone formation and prevent degradation of joint tissues. To our knowledge, however, few joint loading devices are available for clinical or point-of-care applications. Using a voice-coil actuator, we developed an electromechanical loading system appropriate for human studies and preclinical trials that should prove both safe and effective.