Browsing by Author "Utku, Semih"

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Citation - WoS: 2
Citation - Scopus: 6
A robotic system to prepare IV solutions
(Elsevier Ireland Ltd, 2018) Mehmet Suleyman Ünlütürk; Özgür Tamer; Semih Utku; Unluturk, Mehmet S.; Tamer, Ozgur; Utku, Semih
Drugs need to be used regularly and correctly in order to be effective. When medicines are used correctly negativities that threaten human health and life can be avoided but they can cause unwanted situations that can occur until the end of life when they are used incorrectly. The most common drug administration errors in hospitals are: The wrong dosage of the drug given to the patient the timing and / or the method of administration the wrong drug given to the patient the drug given to the wrong patient or even not given. Furthermore the information about the drug that is administered to the patient may not be registered at all. In this research a robotic drug preparation system and a communication server accepting prescription orders have been developed. Component engineering methodology is further utilized in the design of the Drug Preparation System to maximize reuse increase product reliability reduce design code and test efforts. The IV Robotic Drug Preparation Robot is composed of a robotic work station and a Cartesian carrier to carry the work station to the desired location. The robotic work station has several grippers to handle syringes to pull the piston of the syringe and to lock the closed system connector to the vial. The IV Robotic Drug Preparation System and communication server are developed and being used in the hospitals. Due to this system medicines left unused in vials can be used and a great amount of savings is obtained from the drug purchases. © 2018 Elsevier B.V. All rights reserved.
Citation - WoS: 8
Citation - Scopus: 10
Automated personnel-assets-consumables-drug tracking in ambulance services for more effective and efficient medical emergency interventions
(ELSEVIER IRELAND LTD, 2016) Semih Utku; Mehmet Hilal Ozcanhan; Mehmet Suleyman Unluturk; Unluturk, Mehmet Suleyman; Utku, Semih; Özcanhan, Mehmet Hilal
Patient delivery time is no longer considered as the only critical factor in ambulatory services. Presently five clinical performance indicators are used to decide patient satisfaction. Unfortunately the emergency ambulance services in rapidly growing metropolitan areas do not meet current satisfaction expectations, because of human errors in the management of the objects onboard the ambulances. But human involvement in the information management of emergency interventions can be reduced by electronic tracking of personnel assets consumables and drugs (PACD) carried in the ambulances. Electronic tracking needs the support of automation software which should be integrated to the overall hospital information system. Our work presents a complete solution based on a centralized database supported by radio frequency identification (RFID) and bluetooth low energy (BLE) identification and tracking technologies. Each object in an ambulance is identified and tracked by the best suited technology. The automated identification and tracking reduces manual paper documentation and frees the personnel to better focus on medical activities. The presence and amounts of the PACD are automatically monitored warning about their depletion non-presence or maintenance dates. The computerized two way hospital-ambulance communication link provides information sharing and instantaneous feedback for better and faster diagnosis decisions. A fully implemented system is presented with detailed hardware and software descriptions. The benefits and the clinical outcomes of the proposed system are discussed which lead to improved personnel efficiency and more effective interventions. (C) 2015 Elsevier Ireland Ltd. All rights reserved.
Citation - WoS: 5
Citation - Scopus: 6
Neural network-supported patient-adaptive fall prevention system
(Springer, 2020) Mehmet Hilal Özcanhan; Semih Utku; Mehmet Suleyman Ünlütürk; Unluturk, Mehmet Suleyman; Utku, Semih; Özcanhan, Mehmet Hilal
Patient falls due to unattended bed-exits are costly to patients healthcare personnel and hospitals. Numerous researches based on up to three predetermined factors have been conducted for preventing falls. The present comprehensive proposal is based on four sub-systems that synthesize six factors. A parameter is assigned to each factor with a coefficient specifically determined for each individual patient and per admittance. The parameters are aggregated in equations that lead to an early warning about a probable bed-exit or an alarm about an imminent bed-exit. The ultimate aim of our proposal is the generation of the earliest possible warning to grant the longest time for nurse intervention. Thus the probable fall of high-risk patients can be prevented by stopping the unattended bed-exits. The proposal is supported by a prototype multi-tier system design and the results of laboratory patient bed-exit scenarios carried out using the design. Comparison of the obtained results with previous work shows that our proposed solution is unmatched in providing the longest time for nurse intervention (up to 15.7 ± 1.1 s) because of the comprehensive six-factor synthesis specific to each individual patient and each admittance. © 2020 Elsevier B.V. All rights reserved.